PapersAnalysis

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# Overview ## Reinforcement Learning ### Fundamental - [Reinforcement Learning, Fast and Slow](https://github.com/NicolaBernini/PapersAnalysis/issues/20)

NicolaBernini

Container for Various Papers to Read

NicolaBernini

# Overview Basic Information about Quantized and Sparsified Neural Networks

NicolaBernini

# Overview Add Paper Summary for [Visualizing Deep Networks by Optimizing with Integrated Gradients](https://arxiv.org/abs/1905.00954) Reasons - Interesting to add material about CNN Debugging possibly also improving Interpretability

NicolaBernini

Quantum reservoir processing - Analysis

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# Overview Readthrough and Analysis related to [Quantum reservoir processing](https://www.nature.com/articles/s41534-019-0149-8?fbclid=IwAR0yVFxSMDZfOlKcRU8eALBagejVrfuJs_L4N1QfljUgzS4nV-pF84BhuUc)

NicolaBernini

Deep Learning - Basic Elements

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# Overview Basic Elements about Deep Learning

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Generative Models - Basic Elements

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# Overview Basic Elements about Generative Models # TODO - After having it properly extended - [ ] Release as Medium Article

NicolaBernini

# Overview Readthrough of the milestone paper [Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks](https://arxiv.org/abs/1506.01497) as it contains precious intuitions like RPN with important effects on current research

NicolaBernini

Original Paper [Self-Attention Generative Adversarial Networks](https://arxiv.org/abs/1805.08318?fbclid=IwAR2s78qBqrXMkpJpiwQmGbkxTXsqbDesFscnMIes5Muzptc89N56bWELc1A)

NicolaBernini

Capsule Neural Networks for Graph Classification using Explicit Tensorial Graph Representations - ReadThrough

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Original Paper [Capsule Neural Networks for Graph Classification using Explicit Tensorial Graph Representations](https://arxiv.org/abs/1902.08399?fbclid=IwAR1yMDM4cXPrA1TkJa7ODyID_XoREF5rhytEggnV1I9pPsCQ_2p9RN_3cy8)

NicolaBernini