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Generative Adversarial Networks (GAN) can achieve promising performance on learning complex data distributions on different types of data.
A distributed asynchronous relaxation algorithm for the assignment problem
Dimitri P Bertsekas · 1985
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A robust algorithm for point set registration using mixture of gaussians
Bing Jian and Baba C Vemuri · 2005
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Pattern Recognition and Machine Learning
M Christopher Bishop · 2006
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Divergence estimation for multidimensional densities via k k -nearest-neighbor distances
Qing Wang, Sanjeev R Kulkarni, and Sergio Verdú · 2009
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Graph-based segmentation for colored 3d laser point clouds
Johannes Strom, Andrew Richardson, and Edwin Olson · 2010
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Nonparametric divergence estimation with applications to machine learning on distributions
Barnabás Póczos, Liang Xiong, and Jeff Schneider · 2012
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Sinkhorn distances: Lightspeed computation of optimal transport
Marco Cuturi · 2013
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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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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Conditional generative adversarial nets
Mehdi Mirza and Simon Osindero · 2014
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Mlmd: Maximum likelihood mixture decoupling for fast and accurate point cloud registration
Ben Eckart, Kihwan Kim, Alejandro Troccoli, Alonzo Kelly, and Jan Kautz · 2015
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Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian Goodfellow, and Brendan Frey · 2015
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Voxnet: A 3d convolutional neural network for real-time object recognition
Daniel Maturana and Sebastian Scherer · 2015
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Multi-view convolutional neural networks for 3d shape recognition
Hang Su, Subhransu Maji, Evangelos Kalogerakis, and Erik Learned-Miller · 2015
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3d shapenets: A deep representation for volumetric shapes
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
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3d-r2n2: A unified approach for single and multi-view 3d object reconstruction
Christopher B Choy, Danfei Xu, JunYoung Gwak, Kevin Chen, and Silvio Savarese · 2016
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Adversarially learned inference
Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Olivier Mastropietro, Alex Lamb, Martin Arjovsky, and Aaron Courville · 2016
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Professor forcing: A new algorithm for training recurrent networks
Alex M Lamb, Anirudh Goyal ALIAS PARTH GOYAL, Ying Zhang, Saizheng Zhang, Aaron C Courville, and Yoshua Bengio · 2016
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f-gan: Training generative neural samplers using variational divergence minimization
Sebastian Nowozin, Botond Cseke, and Ryota Tomioka · 2016
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Pixel recurrent neural networks
Aaron van den Oord, Nal Kalchbrenner, and Koray Kavukcuoglu · 2016
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Context encoders: Feature learning by inpainting
Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A Efros · 2016
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Volumetric and multi-view cnns for object classification on 3d data
Charles R Qi, Hao Su, Matthias Nießner, Angela Dai, Mengyuan Yan, and Leonidas J Guibas · 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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Generating videos with scene dynamics
Carl Vondrick, Hamed Pirsiavash, and Antonio Torralba · 2016
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Generative image modeling using style and structure adversarial networks
Xiaolong Wang and Abhinav Gupta · 2016
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Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling
Jiajun Wu, Chengkai Zhang, Tianfan Xue, Bill Freeman, and Josh Tenenbaum · 2016
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Seqgan: Sequence generative adversarial nets with policy gradient
FACE Exhibition, 2017
Eunsu Kang · 2017
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Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2017
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Adversarially regularized autoencoders for generating discrete structures
Yoon Kim, Kelly Zhang, Alexander M Rush, Yann LeCun, et al · 2017
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Least squares generative adversarial networks
Xudong Mao, Qing Li, Haoran Xie, Raymond YK Lau, and Zhen Wang · 2017
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Fisher gan
Youssef Mroueh and Tom Sercu · 2017
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Lantao Yu, Weinan Zhang, Jun Wang, and Yong Yu · 2016
Cited alongside, same era.
Energy-based generative adversarial network
Junbo Zhao, Michael Mathieu, and Yann LeCun · 2016
Cited alongside, same era.
Learning representations and generative models for 3d point clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas Guibas · 2017
Cited alongside, same era.
Wasserstein gan
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
Cited alongside, same era.
Generalization and equilibrium in generative adversarial nets (gans)
Sanjeev Arora, Rong Ge, Yingyu Liang, Tengyu Ma, and Yi Zhang · 2017
Cited alongside, same era.
Geometric deep learning: going beyond euclidean data
Michael M Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, and Pierre Vandergheynst · 2017
Cited alongside, same era.
One network to solve them all—solving linear inverse problems using deep projection models
JH Rick Chang, Chun-Liang Li, Barnabas Poczos, BVK Vijaya Kumar, and Aswin C Sankaranarayanan · 2017
Cited alongside, same era.
Youssef Mroueh, Chun-Liang Li, Tom Sercu, Anant Raj, and Yu Cheng · 2017
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Computational optimal transport
Gabriel Peyré, Marco Cuturi, et al · 2017
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The riemannian geometry of deep generative models
Hang Shao, Abhishek Kumar, and P Thomas Fletcher · 2017
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Octree generating networks: Efficient convolutional architectures for high-resolution 3d outputs
Maxim Tatarchenko, Alexey Dosovitskiy, and Thomas Brox · 2017
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Ilya Tolstikhin, Olivier Bousquet, Sylvain Gelly, and Bernhard Schoelkopf · 2017
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Jonathan Weed and Francis Bach · 2017
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Deep sets
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Ruslan R Salakhutdinov, and Alexander J Smola · 2017
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Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
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Gans and unsupervised representation learning, 2018
Yoshua Bengio · 2018
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Learning generative models with sinkhorn divergences
Aude Genevay, Gabriel Peyré, and Marco Cuturi · 2018
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Rotationnet: Joint object categorization and pose estimation using multiviews from unsupervised viewpoints
Asako Kanezaki, Yasuyuki Matsushita, and Yoshifumi Nishida · 2018
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Graphical generative adversarial networks
Chongxuan Li, Max Welling, Jun Zhu, and Bo Zhang · 2018
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Transformation autoregressive networks
Junier B Oliva, Avinava Dubey, Barnabás Póczos, Jeff Schneider, and Eric P Xing · 2018
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Dynamic graph cnn for learning on point clouds
Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E Sarma, Michael M Bronstein, and Justin M Solomon · 2018
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Foldingnet: Point cloud auto-encoder via deep grid deformation
Yaoqing Yang, Chen Feng, Yiru Shen, and Dong Tian · 2018
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