Implementation of papers in 100 lines of code.
- Maxout Networks [arXiv]
- Ian J. Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron Courville, Yoshua Bengio
2013-02-18
- Auto-Encoding Variational Bayes [arXiv]
- Diederik P Kingma, Max Welling
2013-12-20
- Generative Adversarial Networks [arXiv]
- 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 [arXiv]
- Mehdi Mirza, Simon Osindero
2014-11-06
- NICE: Non-linear Independent Components Estimation [arXiv]
- Laurent Dinh, David Krueger, Yoshua Bengio
2014-10-30
- Variational Inference with Normalizing Flows [arXiv]
- Danilo Jimenez Rezende, Shakir Mohamed
2015-05-21
- Convolutional Generative Adversarial Networks [arXiv]
- Alec Radford, Luke Metz, Soumith Chintala
2015-11-19
- Adversarially Learned Inference [arXiv]
- Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Olivier Mastropietro, Alex Lamb, Martin Arjovsky, Aaron Courville
2016-06-02
- Improved Techniques for Training GANs [arXiv]
- Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen
2016-06-10
- Least Squares Generative Adversarial Networks [arXiv]
- Xudong Mao, Qing Li, Haoran Xie, Raymond Y.K. Lau, Zhen Wang, Stephen Paul Smolley
2016-11-13
- Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks [arXiv]
- Chelsea Finn, Pieter Abbeel, Sergey Levine
2017-03-09
- Adversarial Feature Learning [arXiv]
- Jeff Donahue, Philipp Krähenbühl, Trevor Darrell
2017-04-03
- On First-Order Meta-Learning Algorithms [arXiv]
- Alex Nichol, Joshua Achiam, John Schulman
2018-03-08
- Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows [arXiv]
- George Papamakarios, David C. Sterratt, Iain Murray
2018-05-18
- Optimizing Millions of Hyperparameters by Implicit Differentiation [PMLR]
- Jonathan Lorraine, Paul Vicol, David Duvenaud
2019-10-06
- Implicit Neural Representations with Periodic Activation Functions [arXiv]
- Vincent Sitzmann, Julien N. P. Martel, Alexander W. Bergman, David B. Lindell, Gordon Wetzstein
2020-06-17
- Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains [arXiv]
- Matthew Tancik, Pratul P. Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T. Barron, Ren Ng
2020-06-18
- Likelihood-free MCMC with Amortized Approximate Ratio Estimators [PMLR]
- Joeri Hermans, Volodimir Begy, Gilles Louppe
2020-06-26
- NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis [arXiv]
- Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, Ren Ng
2020-08-03
- Multiplicative Filter Networks [OpenReview]
- Rizal Fathony, Anit Kumar Sahu, Devin Willmott, J Zico Kolter
2020-09-28
- FastNeRF: High-Fidelity Neural Rendering at 200FPS [arXiv]
- Stephan J. Garbin, Marek Kowalski, Matthew Johnson, Jamie Shotton, Julien Valentin
2021-03-18
- KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs [arXiv]
- Christian Reiser, Songyou Peng, Yiyi Liao, Andreas Geiger
2021-03-25
- Gromov-Wasserstein Distances between Gaussian Distributions [arXiv]
- Antoine Salmona, Julie Delon, Agnès Desolneux
2021-08-16