Deep learning topic
Deep learning is an AI function and a subset of machine learning, used for processing large amounts of complex data. Deep learning can automatically create algorithms based on data patterns.
ClusterGCN
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
DANMF
A sparsity aware implementation of "Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection" (CIKM 2018).
diff2vec
Reference implementation of Diffusion2Vec (Complenet 2018) built on Gensim and NetworkX.
EdMot
An implementation of "EdMot: An Edge Enhancement Approach for Motif-aware Community Detection" (KDD 2019)
EgoSplitting
A NetworkX implementation of "Ego-splitting Framework: from Non-Overlapping to Overlapping Clusters" (KDD 2017).
FEATHER
The reference implementation of FEATHER from the CIKM '20 paper "Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models".
GraphWaveletNeuralNetwork
A PyTorch implementation of "Graph Wavelet Neural Network" (ICLR 2019)
datacamp
🍧 DataCamp data-science and machine learning courses
deep-learning-notes
🤖 Deep Learning notes and snippets
audiomentations
A Python library for audio data augmentation. Inspired by albumentations. Useful for machine learning.