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Adversarially trained generative models (GANs) have recently achieved compelling image synthesis results.
Incorporating second-order functional knowledge for better option pricing
Charles Dugas, Yoshua Bengio, François Belisle, Claude Nadeau, and Rene Garcia · 2000
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Auto-encoding variational Bayes
Diederik P. Kingma and Max Welling · 2013
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Discriminative unsupervised feature learning with exemplar convolutional neural networks
Alexey Dosovitskiy, Philipp Fischer, Jost Tobias Springenberg, Martin Riedmiller, and Thomas Brox · 2014
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Unsupervised visual representation learning by context prediction
Carl Doersch, Abhinav Gupta, and Alexei A. Efros · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
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Identity mappings in deep residual networks
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Autoencoding beyond pixels using a learned similarity metric
Anders Boesen Lindbo Larsen, Søren Kaae Sønderby, Hugo Larochelle, and Ole Winther · 2016
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Adversarial autoencoders
Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian Goodfellow, and Brendan Frey · 2016
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Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2016
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Improved techniques for training GANs
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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Understanding and improving convolutional neural networks via concatenated rectified linear units
Wenling Shang, Kihyuk Sohn, Diogo Almeida, and Honglak Lee · 2016
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Colorful image colorization
Richard Zhang, Phillip Isola, and Alexei A. Efros · 2016
Cited alongside, same era.
Split-brain autoencoders: Unsupervised learning by cross-channel prediction
Richard Zhang, Phillip Isola, and Alexei A. Efros · 2016
Cited alongside, same era.
Multi-task self-supervised visual learning
Carl Doersch and Andrew Zisserman · 2017
Cited alongside, same era.
Adversarial feature learning
Jeff Donahue, Philipp Krähenbühl, and Trevor Darrell · 2017
Cited alongside, same era.
Adversarially learned inference
Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Olivier Mastropietro, Alex Lamb, Martin Arjovsky, and Aaron Courville · 2017
Cited alongside, same era.
The reversible residual network: Backpropagation without storing activations
Aidan N. Gomez, Mengye Ren, Raquel Urtasun, and Roger B. Grosse · 2017
Unsupervised representation learning by predicting image rotations
Spyros Gidaris, Praveer Singh, and Nikos Komodakis · 2018
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Associative compression networks
Alex Graves, Jacob Menick, and Aäron van den Oord · 2018
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Glow: Generative flow with invertible 1x1 convolutions
Diederik P. Kingma and Prafulla Dhariwal · 2018
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Spectral normalization for generative adversarial networks
Takeru Miyato, Toshiki Kataoka, Masanori Koyama, and Yuichi Yoshida · 2018
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Representation learning with contrastive predictive coding
Aäron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Cited alongside, same era.
GANs trained by a two time-scale update rule converge to a local Nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
Cited alongside, same era.
Jae Hyun Lim and Jong Chul Ye · 2017
Cited alongside, same era.
Learning features by watching objects move
Deepak Pathak, Ross Girshick, Piotr Dollár, Trevor Darrell, and Bharath Hariharan · 2017
Cited alongside, same era.
Open sourcing Sonnet - a new library for constructing neural networks
Malcolm Reynolds, Gabriel Barth-Maron, Frederic Besse, Diego de Las Casas, Andreas Fidjeland, Tim Green, Adrià Puigdomènech, Sébastien Racanière, Jack Rae, and Fabio Viola · 2017
Cited alongside, same era.
Variational approaches for auto-encoding generative adversarial networks
Mihaela Rosca, Balaji Lakshminarayanan, David Warde-Farley, and Shakir Mohamed · 2017
Cited alongside, same era.
Hierarchical implicit models and likelihood-free variational inference
Dustin Tran, Rajesh Ranganath, and David M. Blei · 2017
Cited alongside, same era.
Large scale GAN training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2019
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TF-Replicator: Distributed machine learning for researchers
Peter Buchlovsky, David Budden, Dominik Grewe, Chris Jones, John Aslanides, Frederic Besse, Andy Brock, Aidan Clark, Sergio Gómez Colmenarejo, Aedan Pope, Fabio Viola, and Dan Belov · 2019
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Self-supervised GANs via auxiliary rotation loss
Ting Chen, Xiaohua Zhai, Marvin Ritter, Mario Lucic, and Neil Houlsby · 2019
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Cloud TPU
Google · 2019
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Data-efficient image recognition with contrastive predictive coding
Olivier J. Hénaff, Ali Razavi, Carl Doersch, S. M. Ali Eslami, and Aäron van den Oord · 2019
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Revisiting self-supervised visual representation learning
Alexander Kolesnikov, Xiaohua Zhai, and Lucas Beyer · 2019
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High-fidelity image generation with fewer labels
Mario Lucic, Michael Tschannen, Marvin Ritter, Xiaohua Zhai, Olivier Bachem, and Sylvain Gelly · 2019
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