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爱可可老师一周论文精选
No 1. 《The Matrix Calculus You Need For Deep Learning》 No 2. 《Mapping Text to Knowledge Graph Entities using Multi-Sense LSTMs》 No 3. 《Fusion++: Volumetric Object-Level SLAM》 No 4. 【用深度学习预测大地震余震】 No 5. 《Multi-dimensional Graph Convolutional Networks》 No 6. 《Pairwise Relational Networks for Face Recognition》 No 7. 《R^3-Net: A Deep Network for Multi-oriented Vehicle Detection in Aerial Images and Videos》 No 8. 《Wasserstein is all you need》 No 9. 《Why Self-Attention? A Targeted Evaluation of Neural Machine Translation Architectures》 No 10. 《Convolutional Neural Networks with Recurrent Neural Filters》 No 11. 《Support Neighbor Loss for Person Re-Identification》 No 12. 《Gaussian Word Embedding with a Wasserstein Distance Loss》 No 13. 《Generalisation in humans and deep neural networks》 No 14. 《Generating Text through Adversarial Training using Skip-Thought Vectors》 No 15. 《An elementary introduction to information geometry》 No 16. 《Auto-Classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model》 No 17. 《Simultaneous Localization And Mapping with depth Prediction using Capsule Networks for UAVs》 No 18. 《Learning Neural Templates for Text Generation》 No 19. 《Graph Edit Distance Computation via Graph Neural Networks》 No 20. 《Generating Magnetic Resonance Spectroscopy Imaging Data of Brain Tumours from Linear, Non-Linear and Deep Learning Models》 No 21. 《FPGA Implementation of Convolutional Neural Networks with Fixed-Point Calculations》 No 22. 《Deep Reinforcement Learning in Portfolio Management》 No 23. 《On Tree-Based Neural Sentence Modeling》 No 24. 《Nonconvex Regularization Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learning》 No 25. 《On Deep Neural Networks for Detecting Heart Disease》 No 26. 《Importance Weighting and Varational Inference》 No 27. 《SOLAR: Deep Structured Latent Representations for Model-Based Reinforcement Learning》 No 28. 《Unknown Examples & Machine Learning Model Generalization》 No 29. 《Can 3D Pose be Learned from 2D Projections Alone?》 No 30. 《Cross-view image synthesis using geometry-guided conditional GANs》 No 31. 《A Unified Analysis of Stochastic Momentum Methods for Deep Learning》 No 32. 《Adversarial Sampling for Active Learning》 No 33. 《DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN》 No 34. 《Medical Image Imputation from Image Collections》 No 35. 《Linguistic data mining with complex networks: a stylometric-oriented approach》 No 36. 《Metric Learning for Novelty and Anomaly Detection》 No 37. 《The Scientific Prize Network Predicts Who Pushes the Boundaries of Science》 No 38. 《Bayesian Hidden Markov Tree Models for Clustering Genes with Shared Evolutionary History》 No 39. 《Deep Learning for Energy Markets》 No 40. 《Learning to Compare: Relation Network for Few-Shot Learning》 No 41. 《What Makes Reading Comprehension Questions Easier?》 No 42. 《Use Of Vapnik-Chervonenkis Dimension in Model Selection》 No 43. 《BlockQNN: Efficient Block-wise Neural Network Architecture Generation》 No 44. 《Approximation Trees: Statistical Stability in Model Distillation》 No 45. 《Conceptual Domain Adaptation Using Deep Learning》 No 46. 《Ontology Reasoning with Deep Neural Networks》 No 47. 《DeepDownscale: a Deep Learning Strategy for High-Resolution Weather Forecast》 No 48. 《Improving Abstraction in Text Summarization》 No 49. 《Spectral-Pruning: Compressing deep neural network via spectral analysis》 No 50. 《Revisiting Character-Based Neural Machine Translation with Capacity and Compression》
No 1. 《Notes on Deep Learning for NLP》 No 2. 《Bilinear Attention Networks》 No 3. 《PythonRobotics: a Python code collection of robotics algorithms》 No 4. 《Twin-GAN -- Unpaired Cross-Domain Image Translation with Weight-Sharing GANs》 No 5. 《Towards Effective Deep Embedding for Zero-Shot Learning》 No 6. 《Open Set Chinese Character Recognition using Multi-typed Attributes》 No 7. 《AAD: Adaptive Anomaly Detection through traffic surveillance videos》 No 8. 《Probabilistic Model of Object Detection Based on Convolutional Neural Network》 No 9. 《Deep Lidar CNN to Understand the Dynamics of Moving Vehicles》 No 10. 《A Tree-based Decoder for Neural Machine Translation》 No 11. 《APES: a Python toolbox for simulating reinforcement learning environments》 No 12. 《Bottom-Up Abstractive Summarization》 No 13. 《Hands-on Experience with Gaussian Processes (GPs): Implementing GPs in Python - I》 No 14. 《Total Recall: Understanding Traffic Signs using Deep Hierarchical Convolutional Neural Networks》 No 15. 《Reinforcement Learning for Relation Classification from Noisy Data》 No 16. 《Hyperbolic Recommender Systems》 No 17. 《Retrieve-and-Read: Multi-task Learning of Information Retrieval and Reading Comprehension》 No 18. 《Learning Neural Templates for Text Generation》 No 19. 《Iterative Recursive Attention Model for Interpretable Sequence Classification》 No 20. 《Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text》 No 21. 《Social Network Structure is Predictive of Health and Wellness》 No 22. 《ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions》 No 23. 《Brain Biomarker Interpretation in ASD Using Deep Learning and fMRI》 No 24. 《Interpretation of Natural Language Rules in Conversational Machine Reading》 No 25. 《Multi-Hop Knowledge Graph Reasoning with Reward Shaping》 No 26. 《Dense Pose Transfer》 No 27. 《A Unified Analysis of Stochastic Momentum Methods for Deep Learning》 No 28. 《Choosing How to Choose Papers》 No 29. 《Leveraging Deep Visual Descriptors for Hierarchical Efficient Localization》 No 30. 《Full-body High-resolution Anime Generation with Progressive Structure-conditional Generative Adversarial Networks》
No 1. 《Deep learning for time series classification: a review》 No 2. 《Deep Learning for Generic Object Detection: A Survey》 No 3. 《Data Dropout: Optimizing Training Data for Convolutional Neural Networks》 No 4. 《Semantic Instance Segmentation with a Discriminative Loss Function》 No 5. 【ECCV 2018 Best Paper Award】 No 6. 《Group Normalization》 No 7. 《Semi-supervised Learning on Graphs with Generative Adversarial Nets》 No 8. 《Hyperbolic Recommender Systems》 No 9. 《Brain-Score: Which Artificial Neural Network for Object Recognition is most Brain-Like?》 No 10. 《Hands-on Experience with Gaussian Processes (GPs): Implementing GPs in Python - I》 No 11. 《Bayesian Convolutional Neural Networks》 No 12. 【端到端几何推理发现潜在3D锚点】 No 13. 《Dense Pose Transfer》 No 14. 《PFDet: 2nd Place Solution to Open Images Challenge 2018 Object Detection Track》 No 15. 《TVQA: Localized, Compositional Video Question Answering》 No 16. 《Searching for Efficient Multi-Scale Architectures for Dense Image Prediction》 No 17. 《Embedding Logical Queries on Knowledge Graphs》 No 18. 《An Analysis of Hierarchical Text Classification Using Word Embeddings》 No 19. 《ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks》 No 20. 《Bayesian Semi-supervised Learning with Graph Gaussian Processes》 No 21. 《Five lessons from building a deep neural network recommender》 No 22. 《Learning to Describe Differences Between Pairs of Similar Images》 No 23. 《Learning Sequence Encoders for Temporal Knowledge Graph Completion》 No 24. 《Spherical Latent Spaces for Stable Variational Autoencoders》 No 25. 《Entropy and Graph Energy of Complex Networks》 No 26. 《GANimation: Anatomically-aware Facial Animation from a Single Image》 No 27. 《Deep Depth from Defocus: how can defocus blur improve 3D estimation using dense neural networks?》 No 28. 《Bayesian Nonparametric Spectral Estimation》 No 29. 《Full-body High-resolution Anime Generation with Progressive Structure-conditional Generative Adversarial Networks》 No 30. 《Combined Reinforcement Learning via Abstract Representations》
No 1. 《Softer-NMS: Rethinking Bounding Box Regression for Accurate Object Detection》 No 2. 《Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction》 No 3. 《Random Warping Series: A Random Features Method for Time-Series Embedding》 No 4. 《Faster RER-CNN: application to the detection of vehicles in aerial images》 No 5. 《Human activity recognition based on time series analysis using U-Net》 No 6. 《Deep Clustering for Unsupervised Learning of Visual Features》 No 7. 《Deep Graph Infomax》 No 8. 《Why scatter plots suggest causality, and what we can do about it》 No 9. 《Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding》 No 10. 《Real-Time Monocular Object-Model Aware Sparse SLAM》 No 11. 《No Multiplication? No Floating Point? No Problem! Training Networks for Efficient Inference》 No 12. 《PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume》 No 13. 《A Survey of Learning Causality with Data: Problems and Methods》 No 14. 《On Reinforcement Learning for Full-length Game of StarCraft》 No 15. 《Combined convolutional and recurrent neural networks for hierarchical classification of images》 No 16. 《Time is of the Essence: Machine Learning-based Intrusion Detection in Industrial Time Series Data》 No 17. 【深度学习高精度基因组研究】 No 18. 《VoxelMorph: A Learning Framework for Deformable Medical Image Registration》 No 19. 《LaSOT: A High-quality Benchmark for Large-scale Single Object Tracking》 No 20. 《RPNet: an End-to-End Network for Relative Camera Pose Estimation》 No 21. 《Night-to-Day Image Translation for Retrieval-based Localization》 No 22. 《Multi-View Community Detection in Facebook Public Pages》 No 23. 《Active Anomaly Detection via Ensembles》 No 24. 《Learning to Address Health Inequality in the United States with a Bayesian Decision Network》 No 25. 《A Survey on Theoretical Advances of Community Detection in Networks》 No 26. 《Semi-Supervised Sequence Modeling with Cross-View Training》 No 27. 《WaveCycleGAN: Synthetic-to-natural speech waveform conversion using cycle-consistent adversarial networks》 No 28. 《Temporal Interpolation as an Unsupervised Pretraining Task for Optical Flow Estimation》 No 29. 《Understanding Fake Faces》 No 30. 《Sparsified SGD with Memory》
No 1. 【Airbnb动态定价的定制回归模型】 No 2. 《Real-time 3D Pose Estimation with a Monocular Camera Using Deep Learning and Object Priors On an Autonomous Racecar》 No 3. 《Taming VAEs》 No 4. 《Deep Graph Infomax》 No 5. 《An Introduction to Probabilistic Programming》 No 6. 《How Powerful are Graph Neural Networks?》 No 7. 《Multitask Learning on Graph Neural Networks - Learning Multiple Graph Centrality Measures with a Unified Network》 No 8. 《Global Weighted Average Pooling Bridges Pixel-level Localization and Image-level Classification》 No 9. 《AI Benchmark: Running Deep Neural Networks on Android Smartphones》 No 10. 《Non-local Neural Networks》 No 11. 《Object Detection from Scratch with Deep Supervision》 No 12. 《Combined Image- and World-Space Tracking in Traffic Scenes》 No 13. 《Graph Convolution over Pruned Dependency Trees Improves Relation Extraction》 No 14. 《Learning with Random Learning Rates》 No 15. 《Night-to-Day Image Translation for Retrieval-based Localization》 No 16. 《Unsupervised Person Image Synthesis in Arbitrary Poses》 No 17. 《LaSOT: A High-quality Benchmark for Large-scale Single Object Tracking》 No 18. 《WaveCycleGAN: Synthetic-to-natural speech waveform conversion using cycle-consistent adversarial networks》 No 19. 《Semantic WordRank: Generating Finer Single-Document Summarizations》 No 20. 《A theoretical framework for deep locally connected ReLU network》 No 21. 《Adversarial Attacks and Defences: A Survey》 No 22. 《R-C3D: Region Convolutional 3D Network for Temporal Activity Detection》 No 23. 《Multi-Scale Fully Convolutional Network for Cardiac Left Ventricle Segmentation》 No 24. 《Over-Optimization of Academic Publishing Metrics: Observing Goodhart's Law in Action》 No 25. 《Compressing the Input for CNNs with the First-Order Scattering Transform》 No 26. 《HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering》 No 27. 《Robustness Guarantees for Bayesian Inference with Gaussian Processes》 No 28. 《Dropout Distillation for Efficiently Estimating Model Confidence》 No 29. 《Generative Ensembles for Robust Anomaly Detection》 No 30. 《CPDist: Deep Siamese Networks for Learning Distances Between Structured Preferences》
No 1. 【有助于 科学家 提高写作效率 的 十条简单规则】 No 2. 【今日焦点：Google刷新多项NLP任务的BERT模型】 No 3. 《Unsupervised Learning via Meta-Learning》 No 4. 【RecSys2018 Best Long Paper Award：因果嵌入推荐算法】 No 5. 《Dark Model Adaptation: Semantic Image Segmentation from Daytime to Nighttime》 No 6. 《Multi-Task Learning as Multi-Objective Optimization》 No 7. 《Deep convolutional Gaussian processes》 No 8. 《FashionNet: Personalized Outfit Recommendation with Deep Neural Network》 No 9. 《A Tale of Three Probabilistic Families: Discriminative, Descriptive and Generative Models》 No 10. 《Generative Adversarial Active Learning for Unsupervised Outlier Detection》 No 11. 《Deep clustering: On the link between discriminative models and K-means》 No 12. 《A Multi-Face Challenging Dataset for Robust Face Recognition》 No 13. 《ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design》 No 14. 《Learning to Remember, Forget and Ignore using Attention Control in Memory》 No 15. 《Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs》 No 16. 《Deep processing of structured data》 No 17. 《Training Complex Models with Multi-Task Weak Supervision》 No 18. 《Principal component-guided sparse regression》 No 19. 【用强化学习改进智能体设计】 No 20. 《Projective Inference in High-dimensional Problems: Prediction and Feature Selection》 No 21. 《Bayesian Convolutional Neural Networks with Many Channels are Gaussian Processes》 No 22. 《Analyzing the Noise Robustness of Deep Neural Networks》 No 23. 《GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration》 No 24. 《The Laplacian in RL: Learning Representations with Efficient Approximations》 No 25. 《DeSIGN: Design Inspiration from Generative Networks》 No 26. 【离策略评价估计器设计】 No 27. 《Mining Novel Multivariate Relationships in Time Series Data Using Correlation Networks》 No 28. 《The Blackbird Dataset: A large-scale dataset for UAV perception in aggressive flight》 No 29. 《Interpreting Adversarial Robustness: A View from Decision Surface in Input Space》 No 30. 《Sanity Checks for Saliency Maps》
No 1. 晚安～ No 2. 没错了～ [笑cry] No 3. 【基于PyTorch的开源医学图像处理框架，提供全套的医学成像载入、预处理模块和数据集】 No 4. 原来是这样，很棒的设计！ No 5. 可视化：各个国家的真正大小 src:http://t.cn/E79bUpF ... No 6. 《计算机程序的构造和解释》 No 7. 【(Python)PDF表格数据提取库(提供命令行工具)】 No 8. 《Revisiting RCNN: On Awakening the Classification Power of Faster RCNN》 No 9. No 10. 【(Python)计算机视觉研究基础库】 No 11. 小盆友：“哇！你3D打印了一个‘保存’图标！” No 12. 【Word学术写作指南】 No 13. 2018进度：▓▓▓▓▓▓▓▓▓▓▓▓░░░ 78% ... No 14. 【开源目标检测工具包(PyTorch)】 No 15. [偷笑] No 16. 'BiLSTM-CNN-CRF tagger' by Artem Chernodub GitHub:... No 17. 【今日焦点：Google刷新多项NLP任务的BERT模型】 No 18. 早！ [太阳] No 19. 和狗狗时隔三年重聚的感人时刻 😭 http://t.cn/E79nRhv ... No 20. 今天数学深渊那张图，让不少盆友想起了AI深渊这张图，翻出来大家回味回味... No 21. 【新手试炼：机器学习股市预测】 No 22. 【Python高级应用程序与仪表板解决方案，可整合Bokeh，Matplotlib，HoloViews和其他Python绘图库的交互可视化】 No 23. 【深度学习在转移性乳腺癌检测中的应用】 No 24. 十足科幻风：开上纽约街头的NASA新款火星探测车 [笑而不语] http://t.cn/E7C5w2... No 25. 【斯坦福机器学习课程“CS 229 - Machine Learning”速查表(中文版)】 No 26. 【开源神经网络机器翻译框架OpenNMT的Python实现】 No 27. 【车牌识别API(云服务)】 No 28. 【异常检测学习资源大列表】 No 29. Boss vs. Leader [思考] No 30. 还真是 [笑cry] No 31. 【R语言机器学习入门】 No 32. 《2080 Ti TensorFlow GPU benchmarks - 2080 Ti vs V100 vs 1080 Ti vs Titan V》 No 33. 【spaCy自然语言处理实例指南】 No 34. 【根据平面画像合成3D头发】 No 35. 【MD.ai医学成像深度学习课程资料】 No 36. 《The Way to Go》 No 37. 【不寻常的自编码器】 No 38. 《Bayesian Convolutional Neural Networks with Many Channels are Gaussian Processes》 No 39. 微积分速查 No 40. 《算法工程师手册(数学基础/统计学习/深度学习/自然语言处理/计算机视觉/工具)》 No 41. 【未来的AI产品：设计愈加复杂使用愈加简单】 No 42. 笑容逐渐舒展 [笑cry] No 43. 波士顿动力最新发布的Atlas机器人跳台阶视频：控制软件使用包括腿部、手臂和躯干在内的整个身体来调整... No 44. 【深度学习语义分割概览】 No 45. 《Training Generative Adversarial Networks with Binary Neurons by End-to-end Backpropagation》 No 46. 【基于网页的图像标注工具】 No 47. 【Python封装的Google Tesseract文字识别】 No 48. 'OpenCV-Python-Tutorial 中文版' by No War GitHub: htt... No 49. 《End-to-End Content and Plan Selection for Data-to-Text Generation》 No 50. 《Eyes are the Windows to the Soul: Predicting the Rating of Text Quality Using Gaze Behaviour》
No 1. 【Matplotlib终极指南】 No 2. 《Single-shot real-time femtosecond imaging of temporal focusing》 No 3. 【纯用NumPy实现神经网络】 No 4. ❤️ http://t.cn/E7jQOXU No 5. 警惕所有不提具体任务和数据集、鼓吹“AI(再次/全面)超越人类” No 6. 【用Python/Geopandas/Matplotlib创建gif地图图片】 No 7. 笑容逐渐舒展 [笑cry] No 8. 【异常检测学习资源大列表】 No 9. Boss vs. Leader [思考] No 10. 无监督学习 [哈哈] src:http://t.cn/E7HG0E9 ... No 11. 【GAN的理解与优化】 No 12. 【熵：不确定性度量——八个属性，几个例子和一个定理】 No 13. 【新手试炼：机器学习股市预测】 No 14. 《The Way to Go》 No 15. 【基于网页的图像标注工具】 No 16. 🐰[哈哈] http://t.cn/E7jR1J4 No 17. 【MD.ai医学成像深度学习课程资料】 No 18. 【数据科学家最需要的技能】 No 19. 最近医疗领域深度网络论文大爆发，需要冷静思考：算法验证 ≠ 临床有效性 No 20. 值得AI研究人员思考的街头涂鸦 [思考] ... No 21. 【深度网络与展望：视觉和机器学习】 No 22. 【辛普森的悖论：如何用相同的数据证明相反的论点】 No 23. 【生命之树：生物演化关系示意图，不同半径的扇形代表时间的演进，每个树杈的端点代表一类生物的灭亡】 No 24. 《中国和美国谁能成人工智能领域的领军者？ - 知乎》 No 25. #可可家训# 学会发现和欣赏，愉悦会源源而来；小心痴迷、嫉妒和占有的欲望，懊悔、痛苦和悲伤多源于此。... No 26. 光雕投影(Projection mapping)：也称为立体光雕，是一种投影技术，可以将物体（多半是... No 27. think vs. plan vs. execute [思考] No 28. 【Python封装的Google Tesseract文字识别】 No 29. 晚安～ No 30. 没错了～ [笑cry] No 31. 【Python高级应用程序与仪表板解决方案，可整合Bokeh，Matplotlib，HoloViews和其他Python绘图库的交互可视化】 No 32. Google AI Research的Repo，目前包括(后续应该会发布BERT代码)：- man... No 33. 《FaceBoxes: A CPU Real-time Face Detector with High Accuracy》 No 34. 【TensorFlow的简单易用课程】 No 35. 【nuScenes无人驾驶数据集开发工具集】 No 36. 【基于PyTorch的开源医学图像处理框架，提供全套的医学成像载入、预处理模块和数据集】 No 37. 猎豹尾巴在高速过弯时的用途 http://t.cn/E7Hcnch ... No 38. 【(Python)计算机视觉研究基础库】 No 39. #今日发呆专用# No 40. ANYmal：专注协作的“跟班” No 41. PyTorch Implementation by lxg2015 GitHub:http://t.... No 42. 出个面试题：请问从机器学习角度看这段视频说明什么？ http://t.cn/E7Hx5O6 ... No 43. 《Network Distance Based on Laplacian Flows on Graphs》 No 44. 《Reinforcement Learning for Relation Classification from Noisy Data》 No 45. 原来是这样，很棒的设计！ No 46. 【实体识别数据集集锦】 No 47. 【Keras-MXNet】 No 48. 【Binder 2.0技术指南】 No 49. 【OpenAI Gym推箱子游戏环境】 No 50. 早！ [太阳]
No 1. 【Matplotlib终极指南】 No 2. 《Single-shot real-time femtosecond imaging of temporal focusing》 No 3. 【纯用NumPy实现神经网络】 No 4. ❤️ http://t.cn/E7jQOXU No 5. 警惕所有不提具体任务和数据集、鼓吹“AI(再次/全面)超越人类” No 6. 【用Python/Geopandas/Matplotlib创建gif地图图片】 No 7. 笑容逐渐舒展 [笑cry] No 8. 【异常检测学习资源大列表】 No 9. Boss vs. Leader [思考] No 10. 无监督学习 [哈哈] src:http://t.cn/E7HG0E9 ... No 11. 【GAN的理解与优化】 No 12. 【熵：不确定性度量——八个属性，几个例子和一个定理】 No 13. 【新手试炼：机器学习股市预测】 No 14. 《The Way to Go》 No 15. 【基于网页的图像标注工具】 No 16. 🐰[哈哈] http://t.cn/E7jR1J4 No 17. 【MD.ai医学成像深度学习课程资料】 No 18. 【数据科学家最需要的技能】 No 19. 最近医疗领域深度网络论文大爆发，需要冷静思考：算法验证 ≠ 临床有效性 No 20. 值得AI研究人员思考的街头涂鸦 [思考] ... No 21. 【深度网络与展望：视觉和机器学习】 No 22. 【辛普森的悖论：如何用相同的数据证明相反的论点】 No 23. 【生命之树：生物演化关系示意图，不同半径的扇形代表时间的演进，每个树杈的端点代表一类生物的灭亡】 No 24. 《中国和美国谁能成人工智能领域的领军者？ - 知乎》 No 25. #可可家训# 学会发现和欣赏，愉悦会源源而来；小心痴迷、嫉妒和占有的欲望，懊悔、痛苦和悲伤多源于此。... No 26. 光雕投影(Projection mapping)：也称为立体光雕，是一种投影技术，可以将物体（多半是... No 27. think vs. plan vs. execute [思考] No 28. 【Python封装的Google Tesseract文字识别】 No 29. 晚安～ No 30. 没错了～ [笑cry] No 31. 【Python高级应用程序与仪表板解决方案，可整合Bokeh，Matplotlib，HoloViews和其他Python绘图库的交互可视化】 No 32. Google AI Research的Repo，目前包括(后续应该会发布BERT代码)：- man... No 33. 《FaceBoxes: A CPU Real-time Face Detector with High Accuracy》 No 34. 【TensorFlow的简单易用课程】 No 35. 【nuScenes无人驾驶数据集开发工具集】 No 36. 【基于PyTorch的开源医学图像处理框架，提供全套的医学成像载入、预处理模块和数据集】 No 37. 猎豹尾巴在高速过弯时的用途 http://t.cn/E7Hcnch ... No 38. 【(Python)计算机视觉研究基础库】 No 39. #今日发呆专用# No 40. ANYmal：专注协作的“跟班” No 41. PyTorch Implementation by lxg2015 GitHub:http://t.... No 42. 出个面试题：请问从机器学习角度看这段视频说明什么？ http://t.cn/E7Hx5O6 ... No 43. 《Network Distance Based on Laplacian Flows on Graphs》 No 44. 《Reinforcement Learning for Relation Classification from Noisy Data》 No 45. 原来是这样，很棒的设计！ No 46. 【实体识别数据集集锦】 No 47. 【Keras-MXNet】 No 48. 【Binder 2.0技术指南】 No 49. 【OpenAI Gym推箱子游戏环境】 No 50. 早！ [太阳]
No 1. 《Meta-Learning: A Survey》 No 2. 【有助于 科学家 提高写作效率 的 十条简单规则】 No 3. 《Variational Bayesian Monte Carlo》 No 4. 《The Deep Weight Prior. Modeling a prior distribution for CNNs using generative models》 No 5. 《Poincaré GloVe: Hyperbolic Word Embeddings》 No 6. 《Trellis Networks for Sequence Modeling》 No 7. 《Piano Genie》 No 8. 《Deep Learning for Image Denoising: A Survey》 No 9. 《Sequential Learning of Movement Prediction in Dynamic Environments using LSTM Autoencoder》 No 10. 《Training convolutional neural networks with megapixel images》 No 11. 《Rethinking the Value of Network Pruning》 No 12. 《Adversarial Text Generation Without Reinforcement Learning》 No 13. 《Discriminator Rejection Sampling》 No 14. 《Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications》 No 15. 《Dual Convolutional Neural Network for Graph of Graphs Link Prediction》 No 16. 《Generation Meets Recommendation: Proposing Novel Items for Groups of Users》 No 17. 《Resource-efficient Machine Learning in 2 KB RAM for the Internet of Things》 No 18. 《Q-map: a Convolutional Approach for Goal-Oriented Reinforcement Learning》 No 19. 《Learning and Tracking the 3D Body Shape of Freely Moving Infants from RGB-D sequences》 No 20. 《Approximate Fisher Information Matrix to Characterise the Training of Deep Neural Networks》 No 21. 《SFV: Reinforcement Learning of Physical Skills from Videos》 No 22. 《A Gentle Introduction to Deep Learning in Medical Image Processing》 No 23. 《Realistic Adversarial Examples in 3D Meshes》 No 24. 《Fast deep reinforcement learning using online adjustments from the past》 No 25. 《Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron》 No 26. 《First-order and second-order variants of the gradient descent: a unified framework》 No 27. 《Good Initializations of Variational Bayes for Deep Models》 No 28. 《Gradient Agreement as an Optimization Objective for Meta-Learning》 No 29. 《Deep Imitative Models for Flexible Inference, Planning, and Control》 No 30. 《Brain2Object: Printing Your Mind from Brain Signals with Spatial Correlation Embedding》
No 1. 《A Novel Domain Adaptation Framework for Medical Image Segmentation》 No 2. 《Do Deep Generative Models Know What They Don't Know?》 No 3. 《Deep Learning for Image Denoising: A Survey》 No 4. 《A Social Network Analysis of Articles on Social Network Analysis》 No 5. 《Model Selection Techniques -- An Overview》 No 6. 【今日焦点：Google刷新多项NLP任务的BERT模型】 No 7. 《MaskFusion: Real-Time Recognition, Tracking and Reconstruction of Multiple Moving Objects》 No 8. 《Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach》 No 9. 《Interpretable LSTMs For Whole-Brain Neuroimaging Analyses》 No 10. 《Deep Graph Convolutional Encoders for Structured Data to Text Generation》 No 11. 《Deep Learning with the Random Neural Network and its Applications》 No 12. 《Neighbourhood Consensus Networks》 No 13. 《DGC-Net: Dense Geometric Correspondence Network》 No 14. 《On the Margin Theory of Feedforward Neural Networks》 No 15. 《A Gentle Introduction to Deep Learning in Medical Image Processing》 No 16. 《Applying Deep Learning To Airbnb Search》 No 17. 《Recipe1M: A Dataset for Learning Cross-Modal Embeddings for Cooking Recipes and Food Images》 No 18. 《Dense Object Reconstruction from RGBD Images with Embedded Deep Shape Representations》 No 19. 《Person Retrieval in Surveillance Video using Height, Color and Gender》 No 20. 《Fast deep reinforcement learning using online adjustments from the past》 No 21. 《Contextual Topic Modeling For Dialog Systems》 No 22. 《Gradient Agreement as an Optimization Objective for Meta-Learning》 No 23. 《Good Initializations of Variational Bayes for Deep Models》 No 24. 《First-order and second-order variants of the gradient descent: a unified framework》 No 25. 《Synscapes: A Photorealistic Synthetic Dataset for Street Scene Parsing》 No 26. 《Image Inpainting for Irregular Holes Using Partial Convolutions》 No 27. 《Neural Network Models for Natural Language Inference Fail to Capture the Semantics of Inference》 No 28. 《Image Super-Resolution Using VDSR-ResNeXt and SRCGAN》 No 29. 《From Louvain to Leiden: guaranteeing well-connected communities》 No 30. 《LRW-1000: A Naturally-Distributed Large-Scale Benchmark for Lip Reading in the Wild》
No 1. 《You May Not Need Attention》 No 2. 《Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training》 No 3. 《GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks》 No 4. 《pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference》 No 5. 《Towards Efficient Large-Scale Graph Neural Network Computing》 No 6. 《Sequence classification with human attention》 No 7. 《Dynamic Graph Neural Networks》 No 8. 《CartoonGAN: Generative Adversarial Networks for Photo Cartoonization》 No 9. 《LadderNet: Multi-path networks based on U-Net for medical image segmentation》 No 10. 《WaveGlow: A Flow-based Generative Network for Speech Synthesis》 No 11. 《CatBoost: gradient boosting with categorical features support》 No 12. 《DropBlock: A regularization method for convolutional networks》 No 13. 《Transferrable Feature and Projection Learning with Class Hierarchy for Zero-Shot Learning》 No 14. 《Graph Convolutional Reinforcement Learning for Multi-Agent Cooperation》 No 15. 《Differentiable MPC for End-to-end Planning and Control》 No 16. 《Understanding Deep Convolutional Networks through Gestalt Theory》 No 17. 《Learning Material-Aware Local Descriptors for 3D Shapes》 No 18. 《Textbook Question Answering with Knowledge Graph Understanding and Unsupervised Open-set Text Comprehension》 No 19. 《Humans are still the best lossy image compressors》 No 20. 《A Comparative Study of Fruit Detection and Counting Methods for Yield Mapping in Apple Orchards》 No 21. 《Local Homology of Word Embeddings》 No 22. 《Super-pixel cloud detection using Hierarchical Fusion CNN》 No 23. 《Audio to Body Dynamics》 No 24. 《The Wasserstein transform》 No 25. 《Reversible Recurrent Neural Networks》 No 26. 《Recycle-GAN: Unsupervised Video Retargeting》 No 27. 《A Convolutional Autoencoder Approach to Learn Volumetric Shape Representations for Brain Structures》 No 28. 《Communities as Well Separated Subgraphs With Cohesive Cores: Identification of Core-Periphery Structures in Link Communities》 No 29. 《Automatic differentiation in ML: Where we are and where we should be going》 No 30. 《Dilated DenseNets for Relational Reasoning》
No 1. 《The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale》 No 2. 《Face Recognition: From Traditional to Deep Learning Methods》 No 3. 《WaveGlow: A Flow-based Generative Network for Speech Synthesis》 No 4. 《You Only Search Once: Single Shot Neural Architecture Search via Direct Sparse Optimization》 No 5. 《Language GANs Falling Short》 No 6. 《How deep is deep enough? - Optimizing deep neural network architecture》 No 7. 《Named Entity Disambiguation using Deep Learning on Graphs》 No 8. 《Segmentation of the Proximal Femur from MR Images using Deep Convolutional Neural Networks》 No 9. 《Multi-level Memory for Task Oriented Dialogs》 No 10. 《Modeling Attention Flow on Graphs》 No 11. 《Towards Explainable NLP: A Generative Explanation Framework for Text Classification》 No 12. 《Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension》 No 13. 《Neural Nearest Neighbors Networks》 No 14. 《Do RNNs learn human-like abstract word order preferences?》 No 15. 《Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells》 No 16. 《Simple, Distributed, and Accelerated Probabilistic Programming》 No 17. 《An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution》 No 18. 《Textbook Question Answering with Knowledge Graph Understanding and Unsupervised Open-set Text Comprehension》 No 19. 《Content Selection in Deep Learning Models of Summarization》 No 20. 《How the fundamental concepts of mathematics and physics explain deep learning》 No 21. 《Stochastic Neighbor Embedding under f-divergences》 No 22. 《Towards continual learning in medical imaging》 No 23. 《Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach》 No 24. 《Multi-Agent Common Knowledge Reinforcement Learning》 No 25. 《Generating Photo-Realistic Training Data to Improve Face Recognition Accuracy》 No 26. 《Multiple-Attribute Text Style Transfer》 No 27. 《Scalable Deep kk-Subspace Clustering》 No 28. 《Dilated DenseNets for Relational Reasoning》 No 29. 《You May Not Need Attention》 No 30. 《Finding Mixed Nash Equilibria of Generative Adversarial Networks》
No 1. 《YOLO-LITE: A Real-Time Object Detection Algorithm Optimized for Non-GPU Computers》 No 2. 《Gradient Descent Finds Global Minima of Deep Neural Networks》 No 3. 《DeepMasterPrints: Generating MasterPrints for Dictionary Attacks via Latent Variable Evolution》 No 4. 《Pixel Level Data Augmentation for Semantic Image Segmentation using Generative Adversarial Networks》 No 5. 《Understanding Back-Translation at Scale》 No 6. 《Online Embedding Compression for Text Classification using Low Rank Matrix Factorization》 No 7. 《ImageNet/ResNet-50 Training in 224 Seconds》 No 8. 《Measuring the Effects of Data Parallelism on Neural Network Training》 No 9. 《A Survey on Data Collection for Machine Learning: a Big Data - AI Integration Perspective》 No 10. 《The Price of Fair PCA: One Extra Dimension》 No 11. 《CariGANs: Unpaired Photo-to-Caricature Translation》 No 12. 《Building a Winning Self-Driving Car in Six Months》 No 13. 《Stochastic Normalizations as Bayesian Learning》 No 14. 《Unsupervised image segmentation via maximum a posteriori estimation of continuous max-flow》 No 15. 《Dial2Desc: End-to-end Dialogue Description Generation》 No 16. 《Neural Rendering Model: Joint Generation and Prediction for Semi-Supervised Learning》 No 17. 《Sorting out Lipschitz function approximation》 No 18. 《Bias and Generalization in Deep Generative Models: An Empirical Study》 No 19. 《ExGate: Externally Controlled Gating for Feature-based Attention in Artificial Neural Networks》 No 20. 《Survey on Vision-based Path Prediction》 No 21. 《Neural Music Synthesis for Flexible Timbre Control》 No 22. 《Scale-variant topological information for characterizing complex networks》 No 23. 《Confusion2Vec: Towards Enriching Vector Space Word Representations with Representational Ambiguities》 No 24. 《Benchmarking Deep Sequential Models on Volatility Predictions for Financial Time Series》 No 25. 《Improving End-to-end Speech Recognition with Pronunciation-assisted Sub-word Modeling》 No 26. 《Mesh-TensorFlow: Deep Learning for Supercomputers》 No 27. 《VIREL: A Variational Inference Framework for Reinforcement Learning》 No 28. 《Learning Two Layer Rectified Neural Networks in Polynomial Time》 No 29. 《A Review of automatic differentiation and its efficient implementation》 No 30. 《Exposing DeepFake Videos By Detecting Face Warping Artifacts》
No 1. 《Rethinking ImageNet Pre-training》 No 2. 《YOLO-LITE: A Real-Time Object Detection Algorithm Optimized for Non-GPU Computers》 No 3. 《Orthographic Feature Transform for Monocular 3D Object Detection》 No 4. 《Learning From Positive and Unlabeled Data: A Survey》 No 5. 《Sampling Can Be Faster Than Optimization》 No 6. 《Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection》 No 7. 《Stochastic Deep Networks》 No 8. 《An Introductory Survey on Attention Mechanisms in NLP Problems》 No 9. 《Improving Multi-Person Pose Estimation using Label Correction》 No 10. 《Understanding and Predicting Links in Graphs: A Persistent Homology Perspective》 No 11. 《A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data》 No 12. 《Explaining Deep Learning Models - A Bayesian Non-parametric Approach》 No 13. 《ImageNet/ResNet-50 Training in 224 Seconds》 No 14. 《Forecasting People's Needs in Hurricane Events from Social Network》 No 15. 《Deep Q learning for fooling neural networks》 No 16. 《Multiple People Tracking Using Hierarchical Deep Tracklet Re-identification》 No 17. 《Can Deep Learning Outperform Modern Commercial CT Image Reconstruction Methods?》 No 18. 《Pitfalls of Graph Neural Network Evaluation》 No 19. 《Interactive dimensionality reduction using similarity projections》 No 20. 《Optical Flow Based Background Subtraction with a Moving Camera: Application to Autonomous Driving》 No 21. 《Co-Representation Learning For Classification and Novel Class Detection via Deep Networks》 No 22. 《Bayesian variational inference for exponential random graph models》 No 23. 《Doc2Im: document to image conversion through self-attentive embedding》 No 24. 《NEMGAN: Noise Engineered Mode-matching GAN》 No 25. 《Language GANs Falling Short》 No 26. 《Modular Architecture for StarCraft II with Deep Reinforcement Learning》 No 27. 《A Hierarchical Multi-task Approach for Learning Embeddings from Semantic Tasks》 No 28. 《Image-Level Attentional Context Modeling Using Nested-Graph Neural Networks》 No 29. 《Image Classification at Supercomputer Scale》 No 30. 《The relativistic discriminator: a key element missing from standard GAN》
No 1. 【基因组学深度学习入门】 No 2. 【新任务&数据集：视觉常识推理(VCR)】 No 3. 《Smooth Loss Functions for Deep Top-k Classification》 No 4. 《Dataset Distillation》 No 5. 《Weakly Supervised Semantic Image Segmentation with Self-correcting Networks》 No 6. 【用于视频超分辨率的时间相干GAN(TecoGAN)】 No 7. 《Selective Feature Connection Mechanism: Concatenating Multi-layer CNN Features with a Feature Selector》 No 8. 《How Many Samples are Needed to Learn a Convolutional Neural Network?》 No 9. 《Do GAN Loss Functions Really Matter?》 No 10. 《Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos》 No 11. 《One-Shot Instance Segmentation》 No 12. 《ML-Net: multi-label classification of biomedical texts with deep neural networks》 No 13. 《Partial Convolution based Padding》 No 14. 《Optical Flow Based Background Subtraction with a Moving Camera: Application to Autonomous Driving》 No 15. 《DynamicGEM: A Library for Dynamic Graph Embedding Methods》 No 16. 《Matching Features without Descriptors: Implicitly Matched Interest Points (IMIPs)》 No 17. 《Perturbative Neural Networks》 No 18. 《Short-Term Wind-Speed Forecasting Using Kernel Spectral Hidden Markov Models》 No 19. 【人形机器人分级视觉运动控制】 No 20. 《Guiding the One-to-one Mapping in CycleGAN via Optimal Transport》 No 21. 《Scalable Logo Recognition using Proxies》 No 22. 《Spatio-temporal Stacked LSTM for Temperature Prediction in Weather Forecasting》 No 23. 《Exploiting Sentence Embedding for Medical Question Answering》 No 24. 《An Affect-Rich Neural Conversational Model with Biased Attention and Weighted Cross-Entropy Loss》 No 25. 《Understanding the impact of entropy in policy learning》 No 26. 《A Sufficient Condition for Convergences of Adam and RMSProp》 No 27. 《Sentence Encoding with Tree-constrained Relation Networks》 No 28. 《LinkNet: Relational Embedding for Scene Graph》 No 29. 《Is Data Clustering in Adversarial Settings Secure?》 No 30. 《Understanding and Measuring Psychological Stress using Social Media》
No 1. 《An Introduction to Deep Reinforcement Learning》 No 2. 《Graph-Based Global Reasoning Networks》 No 3. 《Deformable ConvNets v2: More Deformable, Better Results》 No 4. 《Are All Training Examples Created Equal? An Empirical Study》 No 5. 《The Graph-based Broad Behavior-Aware Recommendation System for Interactive News》 No 6. 《Measure, Manifold, Learning, and Optimization: A Theory Of Neural Networks》 No 7. 《ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness》 No 8. 《Optimal Algorithms for Non-Smooth Distributed Optimization in Networks》 No 9. 【视图先验学习单视图3D重建】 No 10. 《Metropolis-Hastings Generative Adversarial Networks》 No 11. 《ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware》 No 12. 《GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism》 No 13. 《Distinguishing correlation from causation using genome-wide association studies》 No 14. 《Learning 3D Human Dynamics from Video》 No 15. 《Neural Ordinary Differential Equations》 No 16. 《Pitfalls of Graph Neural Network Evaluation》 No 17. 《Understanding Unequal Gender Classification Accuracy from Face Images》 No 18. 《Second-order Optimization Method for Large Mini-batch: Training ResNet-50 on ImageNet in 35 Epochs》 No 19. 《Iterative Transformer Network for 3D Point Cloud》 No 20. 《Macro action selection with deep reinforcement learning in StarCraft》 No 21. 《A survey of large-scale reasoning on the Web of data》 No 22. 《Unsupervised Word Discovery with Segmental Neural Language Models》 No 23. 《Seeing in the dark with recurrent convolutional neural networks》 No 24. 《Fashion-Gen: The Generative Fashion Dataset and Challenge》 No 25. 《Multifidelity Approximate Bayesian Computation》 No 26. 《Scan2CAD: Learning CAD Model Alignment in RGB-D Scans》 No 27. 《Multivariate Forecasting of Crude Oil Spot Prices using Neural Networks》 No 28. 《Learning to Reason with Third-Order Tensor Products》 No 29. 《Learning Finite State Representations of Recurrent Policy Networks》 No 30. 《From Context to Concept: Exploring Semantic Relationships in Music with Word2Vec》
No 1. 《Deep Learning on Graphs: A Survey》 No 2. 《ShelfNet for Real-time Semantic Segmentation》 No 3. 《Recent Advances in Autoencoder-Based Representation Learning》 No 4. 《Bag of Tricks for Image Classification with Convolutional Neural Networks》 No 5. 《Bayesian Layers: A Module for Neural Network Uncertainty》 No 6. 《Adversarial Transfer Learning》 No 7. 《Comixify: Transform video into a comics》 No 8. 《CT organ segmentation using GPU data augmentation, unsupervised labels and IOU loss》 No 9. 《Self-Improving Visual Odometry》 No 10. 《Making Classification Competitive for Deep Metric Learning》 No 11. 《Non-delusional Q-learning and value iteration》 No 12. 《A Style-Based Generator Architecture for Generative Adversarial Networks》 No 13. 【大规模AI训练：大批量(Large-Batch)训练实证研究】 No 14. 《A Compact Embedding for Facial Expression Similarity》 No 15. 《Segmentation-driven 6D Object Pose Estimation》 No 16. 《Faster Neural Networks Straight from JPEG》 No 17. 《Graph based Question Answering System》 No 18. 《GaterNet: Dynamic Filter Selection in Convolutional Neural Network via a Dedicated Global Gating Network》 No 19. 《SlowFast Networks for Video Recognition》 No 20. 《Flexible and Scalable State Tracking Framework for Goal-Oriented Dialogue Systems》 No 21. 《General-to-Detailed GAN for Infrequent Class Medical Images》 No 22. 《Context-Aware Synthesis and Placement of Object Instances》 No 23. 《CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks》 No 24. 《Scale-free network clustering in hyperbolic and other random graphs》 No 25. 《Von Mises-Fisher Loss for Training Sequence to Sequence Models with Continuous Outputs》 No 26. 《Dialogue Generation: From Imitation Learning to Inverse Reinforcement Learning》 No 27. 《Deep-RBF Networks Revisited: Robust Classification with Rejection》 No 28. 《Cyber Anomaly Detection Using Graph-node Role-dynamics》 No 29. 《Transferring Knowledge across Learning Processes》 No 30. 《Intra-class Variation Isolation in Conditional GANs》
No 1. 《A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms and Software》 No 2. 《基于知识图谱路径推理的可解释推荐》 No 3. 【大规模AI训练：大批量(Large-Batch)训练实证研究】 No 4. 《Bayesian Optimization in AlphaGo》 No 5. 《A Probe into Understanding GAN and VAE models》 No 6. 《A Comparison of LSTMs and Attention Mechanisms for Forecasting Financial Time Series》 No 7. 《Hierarchical Macro Strategy Model for MOBA Game AI》 No 8. 《Graph Neural Networks: A Review of Methods and Applications》 No 9. 《PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud》 No 10. 《Understanding Individual Decisions of CNNs via Contrastive Backpropagation》 No 11. 《Multi³Net: Segmenting Flooded Buildings via Fusion of Multiresolution, Multisensor, and Multitemporal Satellite Imagery》 No 12. 《A Tutorial on Deep Latent Variable Models of Natural Language》 No 13. 《Dynamic Network Prediction》 No 14. 《On the Dimensionality of Word Embedding》 No 15. 《Guided Zoom: Questioning Network Evidence for Fine-grained Classification》 No 16. 《Taking a Deeper Look at the Inverse Compositional Algorithm》 No 17. 《Generalized Batch Normalization: Towards Accelerating Deep Neural Networks》 No 18. 《Deep Paper Gestalt》 No 19. 《Gaussian Process Deep Belief Networks: A Smooth Generative Model of Shape with Uncertainty Propagation》 No 20. 《Social Network Analysis: Bibliographic Network Analysis of the Field and its Evolution / Part 1. Basic Statistics and Citation Network Analysis》 No 21. 《Anomaly detection with Wasserstein GAN》 No 22. 《Geometrical Stem Detection from Image Data for Precision Agriculture》 No 23. 《SIGNet: Semantic Instance Aided Unsupervised 3D Geometry Perception》 No 24. 《Provable limitations of deep learning》 No 25. 《Top-K Off-Policy Correction for a REINFORCE Recommender System》 No 26. 《AU R-CNN: Encoding Expert Prior Knowledge into R-CNN for Action Unit Detection》 No 27. 《PyText: A Seamless Path from NLP research to production》 No 28. 《Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem》 No 29. 《Detecting rare visual relations using analogies》 No 30. 《Improved Search Strategies for Determining Facial Expression》
No 1. 《Graph Neural Networks: A Review of Methods and Applications》 No 2. 《How Powerful are Graph Neural Networks? 》 No 3. 《CFUN: Combining Faster R-CNN and U-net Network for Efficient Whole Heart Segmentation》 No 4. 《End to End Video Segmentation for Driving : Lane Detection For Autonomous Car》 No 5. 《Wikipedia2Vec: An Optimized Tool for Learning Embeddings of Words and Entities from Wikipedia》 No 6. 《Neural Approaches to Conversational AI》 No 7. 【博士论文：机器人/数据科学层次深度强化学习】 No 8. 《Can VAEs Generate Novel Examples?》 No 9. 《TextBugger: Generating Adversarial Text Against Real-world Applications》 No 10. 《Analysis Methods in Neural Language Processing: A Survey》 No 11. 《ESIR: End-to-end Scene Text Recognition via Iterative Image Rectification》 No 12. 《Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond》 No 13. 《Point Cloud GAN》 No 14. 《Learning Latent Subspaces in Variational Autoencoders》 No 15. 《Sequential Attention GAN for Interactive Image Editing via Dialogue》 No 16. 【看视频将单声道转换成2.5D 立体声的深度学习算法】 No 17. 《Pay Less Attention with Lightweight and Dynamic Convolutions》 No 18. 《The Design and Implementation of XiaoIce, an Empathetic Social Chatbot》 No 19. 《ELASTIC: Improving CNNs with Instance Specific Scaling Policies》 No 20. 《Training Deep Capsule Networks》 No 21. 【LSTM的大批量(Large-Batch)训练】 No 22. 《Machine Learning in Cyber-Security - Problems, Challenges and Data Sets》 No 23. 《Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection》 No 24. 《Modeling the Long Term Future in Model-Based Reinforcement Learning》 No 25. 《Bayesian Meta-network Architecture Learning》 No 26. 《SfMLearner++: Learning Monocular Depth & Ego-Motion using Meaningful Geometric Constraints》 No 27. 《Community structure: A comparative evaluation of community detection methods》 No 28. 《Recurrent Neural Networks with Pre-trained Language Model Embedding for Slot Filling Task》 No 29. 《Combining Deep and Depth: Deep Learning and Face Depth Maps for Driver Attention Monitoring》 No 30. 《RegNet: Learning the Optimization of Direct Image-to-Image Pose Registration》
No 1. 【博士论文：统计与优化——统计学习算法的计算保障】 No 2. 【LSTM的大批量(Large-Batch)训练】 No 3. 【博士论文：元监督视觉学习】 No 4. 《SageDB: A Learned Database》 No 5. 《Neural Model-Based Reinforcement Learning for Recommendation》 No 6. 《Pay Less Attention with Lightweight and Dynamic Convolutions》 No 7. 《Recurrent Neural Networks for Time Series Forecasting》 No 8. 《InstaGAN: Instance-aware Image-to-Image Translation》 No 9. 《The Matrix Calculus You Need For Deep Learning》 No 10. 《EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning》 No 11. 《Looking for ELMo's friends: Sentence-Level Pretraining Beyond Language Modeling》 No 12. 《Visualizing Deep Similarity Networks》 No 13. 《A Comprehensive Survey on Graph Neural Networks》 No 14. 《Improving Generalization and Stability of Generative Adversarial Networks》 No 15. 《Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization》 No 16. 《Multi-class Classification without Multi-class Labels》 No 17. 《BA-Net: Dense Bundle Adjustment Networks》 No 18. 《Temporal Difference Variational Auto-Encoder》 No 19. 《Dynamic Planning Networks》 No 20. 《Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks》 No 21. 《Learning Classifiers with Fenchel-Young Losses: Generalized Entropies, Margins, and Algorithms》 No 22. 《3D Convolution on RGB-D Point Clouds for Accurate Model-free Object Pose Estimation》 No 23. 《Machine learning in resting-state fMRI analysis》 No 24. 《Finger-GAN: Generating Realistic Fingerprint Images Using Connectivity Imposed GAN》 No 25. 《KnockoffGAN: Generating Knockoffs for Feature Selection using Generative Adversarial Networks》 No 26. 《Multiple Sclerosis Lesion Inpainting Using Non-Local Partial Convolutions》 No 27. 《Predicting Aircraft Trajectories: A Deep Generative Convolutional Recurrent Neural Networks Approach》 No 28. 《RegNet: Learning the Optimization of Direct Image-to-Image Pose Registration》 No 29. 《Lagging Inference Networks and Posterior Collapse in Variational Autoencoders》 No 30. 《A Theoretical Analysis of Deep Q-Learning》
No 1. 【医疗深度学习指南(综述)】 No 2. 《A Comprehensive Survey on Graph Neural Networks》 No 3. 《Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context》 No 4. 【BERT句法表示能力实验评测：各项测试均表现出色】 No 5. 《Panoptic Feature Pyramid Networks》 No 6. 【基于深度网络的心脏病专家级动态心电图心律失常检测和分类】 No 7. 《A New Perspective on Machine Learning: How to do Perfect Supervised Learning》 No 8. 《Flow Based Self-supervised Pixel Embedding for Image Segmentation》 No 9. 《On the Dimensionality of Embeddings for Sparse Features and Data》 No 10. 《Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation》 No 11. 《Generative Adversarial Networks for Financial Trading Strategies Fine-Tuning and Combination》 No 12. 《Detecting Text in the Wild with Deep Character Embedding Network》 No 13. 《A Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference》 No 14. 《Dataset Distillation》 No 15. 《What do Language Representations Really Represent?》 No 16. 《Learning Graph Embedding with Adversarial Training Methods》 No 17. 《A Survey on Multi-output Learning》 No 18. 《Attribute-Aware Attention Model for Fine-grained Representation Learning》 No 19. 《Multi-stream CNN based Video Semantic Segmentation for Automated Driving》 No 20. 《3D Point-Capsule Networks》 No 21. 《I Can See Clearly Now : Image Restoration via De-Raining》 No 22. 《Learning Independent Object Motion from Unlabelled Stereoscopic Videos》 No 23. 《Poincaré Wasserstein Autoencoder》 No 24. 《Visualizing Deep Similarity Networks》 No 25. 《Multi-class Classification without Multi-class Labels》 No 26. 《Generalization in Deep Networks: The Role of Distance from Initialization》 No 27. 《Deep Neural Network Approximation Theory》 No 28. 《On Finding Local Nash Equilibria (and Only Local Nash Equilibria) in Zero-Sum Games》 No 29. 《Explanatory Graphs for CNNs》 No 30. 《Explaining AlphaGo: Interpreting Contextual Effects in Neural Networks》
No 1. 《Deep Learning for Anomaly Detection: A Survey》 No 2. 《Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation》 No 3. 《FPGA-based Accelerators of Deep Learning Networks for Learning and Classification: A Review》 No 4. 【让照片里的人物“走两步”：单张图片3D 角色动画合成】 No 5. 《Image Transformation can make Neural Networks more robust against Adversarial Examples》 No 6. 《Eliminating all bad Local Minima from Loss Landscapes without even adding an Extra Unit》 No 7. 《Optimization Models for Machine Learning: A Survey》 No 8. 《GILT: Generating Images from Long Text》 No 9. 《Human few-shot learning of compositional instructions》 No 10. 《Event detection in Twitter: A keyword volume approach》 No 11. 《Active Learning with TensorBoard Projector》 No 12. 《Interpretable machine learning: definitions, methods, and applications》 No 13. 《Identifying and Correcting Label Bias in Machine Learning》 No 14. 《MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks》 No 15. 《DSConv: Efficient Convolution Operator》 No 16. 《Multi-task Learning with Gradient Communication》 No 17. 《Learning-based Optimization of the Under-sampling Pattern in MRI》 No 18. 【用神经进化设计神经网络】 No 19. 《Exploiting Synchronized Lyrics And Vocal Features For Music Emotion Detection》 No 20. 《Interpretable BoW Networks for Adversarial Example Detection》 No 21. 《Understanding the (un)interpretability of natural image distributions using generative models》 No 22. 《Deep Learning for Human Affect Recognition: Insights and New Developments》 No 23. 《Manipulating and Measuring Model Interpretability》 No 24. 《Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context》 No 25. 《The Benefits of Over-parameterization at Initialization in Deep ReLU Networks》 No 26. 《Inference of Demographic Attributes based on Mobile Phone Usage Patterns and Social Network Topology》 No 27. 《Machine Learning at the Wireless Edge: Distributed Stochastic Gradient Descent Over-the-Air》 No 28. 《A Scalable Framework for Acceleration of CNN Training on Deeply-Pipelined FPGA Clusters with Weight and Workload Balancing》 No 29. 【BERT句法表示能力实验评测：各项测试均表现出色】 No 30. 《Unsupervised Moving Object Detection via Contextual Information Separation》
No 1. 【让照片里的人物“走两步”：单张图片3D 角色动画合成】 No 2. 《Artificial Neural Networks》 No 3. 《A Survey of the Recent Architectures of Deep Convolutional Neural Networks》 No 4. 【深度卷积网络高效计算进展】 No 5. 《Attentive Neural Processes》 No 6. 【从图片到涂鸦：高品质涂鸦的自动生成(推断)】 No 7. 《Real-time Joint Object Detection and Semantic Segmentation Network for Automated Driving》 No 8. 《PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume》 No 9. 《CSGAN: Cyclic-Synthesized Generative Adversarial Networks for Image-to-Image Transformation》 No 10. 《Cross-lingual Language Model Pretraining》 No 11. 《Understanding Geometry of Encoder-Decoder CNNs》 No 12. 《Task representations in neural networks trained to perform many cognitive tasks | Nature Neuroscience》 No 13. 《Bayesian Learning of Neural Network Architectures》 No 14. 《AuxNet: Auxiliary tasks enhanced Semantic Segmentation for Automated Driving》 No 15. 《Passage Re-ranking with BERT》 No 16. 《Mono3D++: Monocular 3D Vehicle Detection with Two-Scale 3D Hypotheses and Task Priors》 No 17. 《Good Similar Patches for Image Denoising》 No 18. 《Improved Selective Refinement Network for Face Detection》 No 19. 《A Performance Comparison of Loss Functions for Deep Face Recognition》 No 20. 《FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network》 No 21. 《Soft Rasterizer: Differentiable Rendering for Unsupervised Single-View Mesh Reconstruction》 No 22. 《A Random Walk Approach to First-Order Stochastic Convex Optimization》 No 23. 《Hierarchical Representations with Poincaré Variational Auto-Encoders》 No 24. 《Hierarchical Reinforcement Learning for Multi-agent MOBA Game》 No 25. 《Attention-aware Multi-stroke Style Transfer》 No 26. 《Consistent Optimization for Single-Shot Object Detection》 No 27. 《CT-GAN: Malicious Tampering of 3D Medical Imagery using Deep Learning》 No 28. 《DF-SLAM: A Deep-Learning Enhanced Visual SLAM System based on Deep Local Features》 No 29. 《WALL-E: An Efficient Reinforcement Learning Research Framework》 No 30. 《Understanding Multi-Step Deep Reinforcement Learning: A Systematic Study of the DQN Target》
No 1. 《One-Class Convolutional Neural Network》 No 2. 《The Evolved Transformer》 No 3. 《BioBERT: pre-trained biomedical language representation model for biomedical text mining》 No 4. 《Deep Learning on Small Datasets without Pre-Training using Cosine Loss》 No 5. 《A BERT Baseline for the Natural Questions》 No 6. 【综述：大脑误差反向传播理论】 No 7. 《Glyce: Glyph-vectors for Chinese Character Representations》 No 8. 《Hotels-50K: A Global Hotel Recognition Dataset》 No 9. 《Fixup Initialization: Residual Learning Without Normalization》 No 10. 《Self-Supervised Generalisation with Meta Auxiliary Learning》 No 11. 《MONet: Unsupervised Scene Decomposition and Representation》 No 12. 《Disentangling Disentanglement in Variational Auto-Encoders》 No 13. 《Design of Real-time Semantic Segmentation Decoder for Automated Driving》 No 14. 《Random Forest with Learned Representations for Semantic Segmentation》 No 15. 《In Defense of the Triplet Loss for Visual Recognition》 No 16. 《Joint shape learning and segmentation for medical images using a minimalistic deep network》 No 17. 《Theoretically Principled Trade-off between Robustness and Accuracy》 No 18. 《Spatial-Temporal Graph Convolutional Networks for Sign Language Recognition》 No 19. 《Hierarchical Attentional Hybrid Neural Networks for Document Classification》 No 20. 《Towards a Deeper Understanding of Adversarial Losses》 No 21. 《Chester: A Web Delivered Locally Computed Chest X-Ray Disease Prediction System》 No 22. 《Self-Supervised Deep Image Denoising》 No 23. 《What does the free energy principle tell us about the brain?》 No 24. 《Predicting Parkinson's Disease using Latent Information extracted from Deep Neural Networks》 No 25. 《Hierarchically Clustered Representation Learning》 No 26. 《Max-margin Class Imbalanced Learning with Gaussian Affinity》 No 27. 《Fast Markov Chain Monte Carlo Algorithms via Lie Groups》 No 28. 《Evaluating the State-of-the-Art of End-to-End Natural Language Generation: The E2E NLG Challenge》 No 29. 《Reward Shaping via Meta-Learning》 No 30. 《Active Anomaly Detection via Ensembles: Insights, Algorithms, and Interpretability》
No 1. 《Visual SLAM: Why Bundle Adjust?》 No 2. 《Improved Knowledge Distillation via Teacher Assistant: Bridging the Gap Between Student and Teacher》 No 3. 《Impact of Fully Connected Layers on Performance of Convolutional Neural Networks for Image Classification》 No 4. 《Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet》 No 5. 【浏览器里的胸片自动诊断工具(本地运行，保护隐私)】 No 6. 《Graph Classification with Recurrent Variational Neural Networks》 No 7. 《EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks》 No 8. 《CHIP: Channel-wise Disentangled Interpretation of Deep Convolutional Neural Networks》 No 9. 《A Multi-Resolution Word Embedding for Document Retrieval from Large Unstructured Knowledge Bases》 No 10. 《Real-time 3D Traffic Cone Detection for Autonomous Driving》 No 11. 《Scaling computational genomics to millions of individuals with GPUs》 No 12. 《A Simple Baseline for Bayesian Uncertainty in Deep Learning》 No 13. 《Natural Language Processing, Sentiment Analysis and Clinical Analytics》 No 14. 《Beholder-GAN: Generation and Beautification of Facial Images with Conditioning on Their Beauty Level》 No 15. 《Multi-dimensional Tensor Sketch》 No 16. 《Word Embeddings for Sentiment Analysis: A Comprehensive Empirical Survey》 No 17. 《Deep Reinforcement Learning from Policy-Dependent Human Feedback》 No 18. 《SiamVGG: Visual Tracking using Deeper Siamese Networks》 No 19. 《Stochastic Gradient Descent Escapes Saddle Points Efficiently》 No 20. 《Task2Vec: Task Embedding for Meta-Learning》 No 21. 《BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model》 No 22. 《Conditional BERT Contextual Augmentation》 No 23. 《The role of a layer in deep neural networks: a Gaussian Process perspective》 No 24. 《Advances on CNN-based super-resolution of Sentinel-2 images》 No 25. 《Generalized Sliced Wasserstein Distances》 No 26. 《DFuseNet: Deep Fusion of RGB and Sparse Depth Information for Image Guided Dense Depth Completion》 No 27. 《Unsupervised Data Uncertainty Learning in Visual Retrieval Systems》 No 28. 《Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation》 No 29. 《Negative eigenvalues of the Hessian in deep neural networks》 No 30. 《Mean Field Limit of the Learning Dynamics of Multilayer Neural Networks》
No 1. 【基于GAN的人脸照片涂鸦编辑，可添加/更改耳环，眼镜，发型，酒窝等】 No 2. 《Fast-SCNN: Fast Semantic Segmentation Network》 No 3. 《Fake News Detection on Social Media using Geometric Deep Learning》 No 4. 《Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent》 No 5. 《Augmentation for small object detection》 No 6. 《Contextual Word Representations: A Contextual Introduction》 No 7. 《DeeperLab: Single-Shot Image Parser》 No 8. 《On the Impact of the Activation Function on Deep Neural Networks Training》 No 9. 《AdaScale: Towards Real-time Video Object Detection Using Adaptive Scaling》 No 10. 《Deep Learning for Image Super-resolution: A Survey》 No 11. 《Simplifying Graph Convolutional Networks》 No 12. 《ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing》 No 13. 【深度流体：GAN参数化流体模拟】 No 14. 《Do ImageNet Classifiers Generalize to ImageNet?》 No 15. 《Context-Aware Self-Attention Networks》 No 16. 《A Simple Method for Commonsense Reasoning》 No 17. 《A Generalized Framework for Population Based Training》 No 18. 《Heartbeat Anomaly Detection using Adversarial Oversampling》 No 19. 《BigEarthNet: A Large-Scale Benchmark Archive For Remote Sensing Image Understanding》 No 20. 《Probabilistic Neural Architecture Search》 No 21. 《On Evaluating Adversarial Robustness》 No 22. 《Seven Myths in Machine Learning Research》 No 23. 《Heavy-tailed kernels reveal a finer cluster structure in t-SNE visualisations》 No 24. 《Learning interpretable continuous-time models of latent stochastic dynamical systems》 No 25. 《Heterogeneous Edge Embeddings for Friend Recommendation》 No 26. 《Discovery of Natural Language Concepts in Individual Units of CNNs》 No 27. 《World Discovery Models》 No 28. 《An attention based deep learning model of clinical events in the intensive care unit》 No 29. 《A Theory of Selective Prediction》 No 30. 《Fast Efficient Hyperparameter Tuning for Policy Gradients》
No 1. 《Parsing Gigabytes of JSON per Second》 No 2. 【Bio-LSTM人体运动(姿态/步法)预测】 No 3. 《Deep High-Resolution Representation Learning for Human Pose Estimation》 No 4. 《GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction》 No 5. 《Spreading vectors for similarity search》 No 6. 【曲率正则化与鲁棒性的双向增强：对抗训练可有效提高分类器鲁棒性，其几何表征非常简单，基于此反向设计有效的正则化提高对抗性】 No 7. 《GeoGAN: A Conditional GAN with Reconstruction and Style Loss to Generate Standard Layer of Maps from Satellite Images》 No 8. 【基于GAN的人脸照片涂鸦编辑，可添加/更改耳环，眼镜，发型，酒窝等】 No 9. 《PIXOR: Real-time 3D Object Detection from Point Clouds》 No 10. 《Bayesian Anomaly Detection and Classification》 No 11. 《Adaptive Gradient Methods with Dynamic Bound of Learning Rate(AdaBound)》 No 12. 《Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling》 No 13. 《A Study on Graph-Structured Recurrent Neural Networks and Sparsification with Application to Epidemic Forecasting》 No 14. 《BigEarthNet: A Large-Scale Benchmark Archive For Remote Sensing Image Understanding》 No 15. 《Online Meta-Learning》 No 16. 《A Mean Field Theory of Batch Normalization》 No 17. 《Attention is not Explanation》 No 18. 《Ising-Dropout: A Regularization Method for Training and Compression of Deep Neural Networks》 No 19. 《The State of Sparsity in Deep Neural Networks》 No 20. 《Financial series prediction using Attention LSTM》 No 21. 《Online Multi-Object Tracking with Instance-Aware Tracker and Dynamic Model Refreshment》 No 22. 《Robust Graph Embedding with Noisy Link Weights》 No 23. 《Scalable Hyperbolic Recommender Systems》 No 24. 【生物神经网络与人工神经网络分析：协同的挑战和机遇？】 No 25. 《Box-level Segmentation Supervised Deep Neural Networks for Accurate and Real-time Multispectral Pedestrian Detection》 No 26. 《GANSynth: Adversarial Neural Audio Synthesis》 No 27. 《The State of the Art in Multilayer Network Visualization》 No 28. 《LocalNorm: Robust Image Classification through Dynamically Regularized Normalization》 No 29. 《Transfusion: Understanding Transfer Learning with Applications to Medical Imaging》 No 30. 《GSLAM: A General SLAM Framework and Benchmark》
No 1. 《Attention is not Explanation》 No 2. 《Financial series prediction using Attention LSTM》 No 3. 《Insights into LSTM Fully Convolutional Networks for Time Series Classification》 No 4. 《High-Fidelity Image Generation With Fewer Labels》 No 5. 《Learning where to look: Semantic-Guided Multi-Attention Localization for Zero-Shot Learning》 No 6. 《Detecting Overfitting via Adversarial Examples》 No 7. 《A Joint Deep Learning Approach for Automated Liver and Tumor Segmentation》 No 8. 《Data augmentation using learned transforms for one-shot medical image segmentation》 No 9. 《VideoFlow: A Flow-Based Generative Model for Video》 No 10. 《Degenerate Feedback Loops in Recommender Systems》 No 11. 《Evaluating Feature Importance Estimates》 No 12. 《Video Face Recognition: Component-wise Feature Aggregation Network (C-FAN)》 No 13. 《Fast Graph Representation Learning with PyTorch Geometric》 No 14. 《Structure Tree-LSTM: Structure-aware Attentional Document Encoders》 No 15. 《Learning a smooth kernel regularizer for convolutional neural networks》 No 16. 《Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach》 No 17. 《Comparison of Deep Neural Networks and Deep Hierarchical Models for Spatio-Temporal Data》 No 18. 《DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs》 No 19. 《Adversarial Attacks on Time Series》 No 20. 《A comparative evaluation of novelty detection algorithms for discrete sequences》 No 21. 《Evolutionary Neural AutoML for Deep Learning》 No 22. 《Efficient Contextual Representation Learning Without Softmax Layer》 No 23. 《Large-Scale Object Mining for Object Discovery from Unlabeled Video》 No 24. 《Entity Recognition at First Sight: Improving NER with Eye Movement Information》 No 25. 《A Mean Field Theory of Batch Normalization》 No 26. 《Nonlinear Markov Random Fields Learned via Backpropagation》 No 27. 《Learning to Plan via Neural Exploration-Exploitation Trees》 No 28. 《Using Natural Language for Reward Shaping in Reinforcement Learning》 No 29. 《ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shape》 No 30. 《Automated Model Selection with Bayesian Quadrature》
No 1. 《A Mean Field Theory of Batch Normalization》 No 2. 《Gradient Descent based Optimization Algorithms for Deep Learning Models Training》 No 3. 《Efficient Parameter-free Clustering Using First Neighbor Relations》 No 4. 《Deep CNN-based Multi-task Learning for Open-Set Recognition》 No 5. 《Theory III: Dynamics and Generalization in Deep Networks》 No 6. 《Financial Applications of Gaussian Processes and Bayesian Optimization》 No 7. 《Graph Colouring Meets Deep Learning: Effective Graph Neural Network Models for Combinatorial Problems》 No 8. 《GanDef: A GAN based Adversarial Training Defense for Neural Network Classifier》 No 9. 《Hierarchical Autoregressive Image Models with Auxiliary Decoders》 No 10. 《The Evolved Transformer》 No 11. 《Ranked List Loss for Deep Metric Learning》 No 12. 《Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation》 No 13. 《When random search is not enough: Sample-Efficient and Noise-Robust Blackbox Optimization of RL Policies》 No 14. 《Learning deep neural networks in blind deblurring framework》 No 15. 《Neural Language Modeling with Visual Features》 No 16. 《Graph-RISE: Graph-Regularized Image Semantic Embedding》 No 17. 《Why Learning of Large-Scale Neural Networks Behaves Like Convex Optimization》 No 18. 《Discovering Visual Patterns in Art Collections with Spatially-consistent Feature Learning》 No 19. 《A Survey on Graph Processing Accelerators: Challenges and Opportunities》 No 20. 《3DN: 3D Deformation Network》 No 21. 《The principles of adaptation in organisms and machines I: machine learning, information theory, and thermodynamics》 No 22. 《A Machine Learning Dataset Prepared From the NASA Solar Dynamics Observatory Mission》 No 23. 《Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation》 No 24. 《Unsupervised Domain Adaptation using Feature-Whitening and Consensus Loss》 No 25. 《Deep Embeddings for Rare Audio Event Detection With Imbalanced Data》 No 26. 《GCNv2: Efficient Correspondence Prediction for Real-Time SLAM》 No 27. 《RGBD Based Dimensional Decomposition Residual Network for 3D Semantic Scene Completion》 No 28. 《Context-Aware Learning for Neural Machine Translation》 No 29. 《PanopticFusion: Online Volumetric Semantic Mapping at the Level of Stuff and Things》 No 30. 《RVOS: End-to-End Recurrent Network for Video Object Segmentation》