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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.
Implementation of papers in 100 lines of code.
| Date | Stars |
|---|---|
| 2026-07-24 | 2837 |
| 2026-07-25 | 2838 |
| 2026-07-28 | 2838 |
| 2026-07-30 | 2838 |
| 2026-08-06 | 2838 |
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 [](https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/blob/master/README.md) [](https://opensource.org/licenses/MIT) # Papers in 100 Lines of Code Implementation of papers in 100 lines of code. ## Implemented papers ##### [Maxout Networks] - Maxout Networks [[arXiv]](https://arxiv.org/abs/1302.4389) - *Ian J. Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron Courville, Yoshua Bengio* - `2013-02-18` ##### [Network In Network] - Network In Network [[arXiv]](https://arxiv.org/abs/1312.4400) - *Min Lin, Qiang Chen, Shuicheng Yan* - `2013-12-13` ##### [Playing Atari with Deep Reinforcement Learning] - Playing Atari with Deep Reinforcement Learning [[arXiv]](https://arxiv.org/abs/1312.5602) - *Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, Martin Riedmiller* - `2013-12-19` ##### [Auto-Encoding Variational Bayes] - Auto-Encoding Variational Bayes [[arXiv]](https://arxiv.org/abs/1312.6114) - *Diederik P Kingma, Max Welling* - `2013-12-20` ##### [Generative Adversarial Networks] - Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1406.2661) - *Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio* - `2014-06-10` ##### [Conditional Generative Adversarial Nets] - Conditional Generative Adversarial Nets [[arXiv]](https://arxiv.org/abs/1411.1784) - *Mehdi Mirza, Simon Osindero* - `2014-11-06` ##### [Adam: A Method for Stochastic Optimization] - Adam: A Method for Stochastic Optimization [[arXiv]](https://arxiv.org/abs/1412.6980) - *Diederik P. Kingma, Jimmy Ba* - `2014-12-22` ##### [NICE: Non-linear Independent Components Estimation] - NICE: Non-linear Independent Components Estimation [[arXiv]](https://arxiv.org/abs/1410.8516) - *Laurent Dinh, David Krueger, Yoshua Bengio* - `2014-10-30` ##### [Human-level control through deep reinforcement learning] - Human-level control through deep reinforcement learning [[nature]](https://www.nature.com/articles/nature14236) - *Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller, Andreas K. Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg & Demis Hassabis* - `2015-02-25` ##### [Deep Unsupervised Learning using Nonequilibrium Thermodynamics] - Deep Unsupervised Learning using Nonequilibrium Thermodynamics [[arXiv]](https://arxiv.org/abs/1503.03585) - *Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, Surya Ganguli* - `2015-03-12` ##### [Variational Inference with Normalizing Flows] - Variational Inference with Normalizing Flows [[arXiv]](https://arxiv.org/abs/1505.05770) - *Danilo Jimenez Rezende, Shakir Mohamed* - `2015-05-21` ##### [Deep Reinforcement Learning with Double Q-learning] - Deep Reinforcement Learning with Double Q-learning [[arXiv]](https://arxiv.org/abs/1509.06461) - *Hado van Hasselt, Arthur Guez, David Silver* - `2015-09-22` ##### [Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks] - Convolutional Generative Adversarial Networks [[arXiv]](https://arxiv.org/abs/1511.06434) - *Alec Radford, Luke Metz, Soumith Chintala* - `2015-11-19` ##### [Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)] - Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) [[arXiv]](https://arxiv.org/abs/1511.07289) - *Djork-Arné Clevert, Thomas Unterthiner, Sepp Hochreiter* - `2015-11-23` ##### [Adversarially Learned Inference] - Adversarially Learned Inference [[arXiv]](https://arxiv.org/abs/1606.00704) - *Vincent Dumoulin, Ishmael Belghazi, Ben Poole
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Maxime Vandegar
118
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Mayuresh Dharwadkar · @infineon · India
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Janosh Riebesell · @periodiclabs · United States
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Ajay Gonepuri (GONAPCORP)
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:3ffc9027521143c8, topic:reinforcement-learning, topic:rl, readme:reinforcement learning
matched fp:3ffc9027521143c8, topic:deep-learning, topic:pytorch
matched fp:3ffc9027521143c8, topic:nerf
matched fp:3ffc9027521143c8, topic:papers, topic:educational