Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
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| 2026-08-05 | 1994 |
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| 2026-11-03 | 1998 |
| 2026-11-04 | 1998 |
Today
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This week
+2 stars this week
This month
+4 stars this month
Momentum
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growth rate 0.10%/day
# neural-network-papers ## Table of Contents 1. [Other Lists](#other-lists) 2. [Surveys](#surveys) 3. [Books](#books) 4. [Datasets](#datasets) 5. [Pretrained Models](#pretrained-models) 6. [Programming Frameworks](#programming-frameworks) 7. [Learning to Compute](#learning-to-compute) 8. [Natural Language Processing](#natural-language-processing) 9. [Convolutional Neural Networks](#convolutional-neural-networks) 10. [Recurrent Neural Networks](#recurrent-neural-networks) 11. [Convolutional Recurrent Neural Networks](#convolutional-recurrent-neural-networks) 12. [Adversarial Neural Networks](#adversarial-neural-networks) 12. [Autoencoders](#autoencoders) 13. [Restricted Boltzmann Machines](#restricted-boltzmann-machines) 14. [Biologically Plausible Learning](#biologically-plausible-learning) 15. [Supervised Learning](#supervised-learning) 16. [Unsupervised Learning](#unsupervised-learning) 17. [Reinforcement Learning](#reinforcement-learning) 18. [Theory](#theory) 19. [Quantum Computing](#quantum-computing) 20. [Training Innovations](#training-innovations) 21. [Parallel Training](#parallel-training) 22. [Weight Compression](#weight-compression) 23. [Numerical Precision](#numerical-precision) 24. [Numerical Optimization](#numerical-optimization) 25. [Motion Planning](#motion-planning) 26. [Simulation](#simulation) 27. [Hardware](#hardware) 28. [Cognitive Architectures](#cognitive-architectures) 29. [Computational Creativity](#computational-creativity) 30. [Cryptography](#cryptography) 31. [Distributed Computing](#distributed-computing) 32. [Clustering](#clustering) ## Other Lists * [DeepLearning.University – An Annotated Deep Learning Bibliography | Memkite](http://memkite.com/deep-learning-bibliography/ "Amund Tveit") ([github.com/memkite/DeepLearningBibliography](https://github.com/memkite/DeepLearningBibliography)) * [Deep Learning for NLP resources](https://github.com/andrewt3000/DL4NLP "Andrew Thomas") * [Reading List « Deep Learning](http://deeplearning.net/reading-list/ "Caglar Gulcehre et al.") * [Reading lists for new MILA students](https://docs.google.com/document/d/1IXF3h0RU5zz4ukmTrVKVotPQypChscNGf5k6E25HGvA/edit "Institut des algorithmes d'apprentissage de Montréal (Montreal Institute for Learning Algorithms)") * [Awesome Recurrent Neural Networks](https://github.com/kjw0612/awesome-rnn "Jiwon Kim") * [Awesome Deep Learning](https://github.com/ChristosChristofidis/awesome-deep-learning "Christos Christofidis") * [Deep learning Reading List](http://jmozah.github.io/links/ "J Mohamed Zahoor") * [A curated list of speech and natural language processing resources](https://medium.com/@joshdotai/a-curated-list-of-speech-and-natural-language-processing-resources-4d89f94c032a "Paul Dixon") ([github.com/edobashira/speech-language-processing](https://github.com/edobashira/speech-language-processing)) * [CS089/CS189 | Deep Learning | Spring 2015](http://www.cs.dartmouth.edu/~lorenzo/teaching/cs189/readinglist.html "Lorenzo Torresani") ## Surveys * [Deep Learning](http://rdcu.be/cW4c "Yann LeCunn, Yoshua Bengio, Geoffrey Hinton") * [Deep Learning in Neural Networks: An Overview](http://arxiv.org/abs/1404.7828 "Juergen Schmidhuber") * [Deep neural networks: a new framework for modelling biological vision and brain information processing](http://biorxiv.org/content/biorxiv/early/2015/10/26/029876.abstract "Nikolaus Kriegeskorte") * [A Primer on Neural Network Models for Natural Language Processing](http://u.cs.biu.ac.il/~yogo/nnlp.pdf "Yoav Goldberg") * [Natural Language Understanding with Distributed Representation](http://arxiv.org/abs/1511.07916 "Kyunghyun Cho") ## Books * [Deep Learning](http://www.iro.umontreal.ca/~bengioy/dlbook/ "Yoshua Bengio, Ian J. Goodfellow, Aaron Courville") * [Neural Networks and Deep Learning](http://neuralnetworksanddeeplearning.com/ "Michael Nielsen") ## Datasets * [Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks](http://arxiv.org/abs/1502.05698 "Jason Weston, Antoine
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:2bee5c5c167dea55, llm:Repository name 'neural-network-papers' and topic 'awesome-lists' indicate a curated list of neural network research papers (no code). Description/readme empty but name implies collection of papers related to neural networks.
