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awesome deep generative models papers
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List: awesome-DGM-papers

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awesome deep generative models papers

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# awesome-DGM-papers



Conference papers on deep generative models.



## ICLR 2020



### Oral



- [Your Classifier is Secretly an Energy based Model and You Should Treat it Like One](https://openreview.net/forum?id=Hkxzx0NtDB), Will Grathwohl, Kuan-Chieh Wang, Joern-Henrik Jacobsen, David Duvenaud, Mohammad Norouzi, Kevin Swersky

- [High Fidelity Speech Synthesis with Adversarial Networks](https://openreview.net/forum?id=r1gfQgSFDr), Mikołaj Bińkowski, Jeff Donahue, Sander Dieleman, Aidan Clark, Erich Elsen, Norman Casagrande, Luis C. Cobo, Karen Simonyan



### Spotlight



- [Stable Rank Normalization for Improved Generalization in Neural Networks and GANs](https://openreview.net/forum?id=H1enKkrFDB), Amartya Sanyal, Philip H. Torr, Puneet K. Dokania

- [Scaling Autoregressive Video Models](https://openreview.net/forum?id=rJgsskrFwH), Dirk Weissenborn, Oscar Täckström, Jakob Uszkoreit



### Poster

- [AE-OT: A New Generative Model based on Extended Semi-Discrete Optimal Transport](https://openreview.net/forum?id=HkldyTNYwH), Dongsheng An, Yang Guo, Na Lei, Zhongxuan Luo, Shing-Tung Yau, Xianfeng Gu

- [Input Complexity and Out-of-distribution Detection with Likelihood-based Generative Models](https://openreview.net/forum?id=SyxIWpVYvr), Joan Serrà, David Álvarez, Vicenç Gómez, Olga Slizovskaia, José F. Núñez, Jordi Luque

- [VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation](https://openreview.net/forum?id=rJgUfTEYvH), Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, Durk Kingma

- [Difference-Seeking Generative Adversarial Network--Unseen Sample Generation](https://openreview.net/forum?id=rygjmpVFvB), Yi Lin Sung, Sung-Hsien Hsieh, Soo-Chang Pei, Chun-Shien Lu

- [From Variational to Deterministic Autoencoders](https://openreview.net/forum?id=S1g7tpEYDS), Partha Ghosh, Mehdi S. M. Sajjadi, Antonio Vergari, Michael Black, Bernhard Scholkopf

- [Generative Ratio Matching Networks](https://openreview.net/forum?id=SJg7spEYDS), Akash Srivastava, Kai Xu, Michael U. Gutmann, Charles Sutton

- [On the "Steerability" of Generative Adversarial Networks](https://openreview.net/forum?id=HylsTT4FvB), Ali Jahanian*, Lucy Chai*, Phillip Isola

- [Semi-Supervised Generative Modeling for Controllable Speech Synthesis](https://openreview.net/forum?id=rJeqeCEtvH), Raza Habib, Soroosh Mariooryad, Matt Shannon, Eric Battenberg, RJ Skerry-Ryan, Daisy Stanton, David Kao, Tom Bagby

- [Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets](https://openreview.net/forum?id=SJxIm0VtwH), Mingrui Liu, Youssef Mroueh, Jerret Ross, Wei Zhang, Xiaodong Cui, Payel Das, Tianbao Yang

- [Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling](https://openreview.net/forum?id=H1x5wRVtvS), Hao Zhang, Bo Chen, Long Tian, Zhengjue Wang, Mingyuan Zhou

- [On the Need for Topology-Aware Generative Models for Manifold-Based Defenses](https://openreview.net/forum?id=r1lF_CEYwS), Uyeong Jang, Susmit Jha, Somesh Jha

- [A Closer Look at the Optimization Landscapes of Generative Adversarial Networks](https://openreview.net/forum?id=HJeVnCEKwH), Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien

- [Generative Models for Effective ML on Private, Decentralized Datasets](https://openreview.net/forum?id=SJgaRA4FPH), Sean Augenstein, H. Brendan McMahan, Daniel Ramage, Swaroop Ramaswamy, Peter Kairouz, Mingqing Chen, Rajiv Mathews, Blaise Aguera y Arcas

- [Smoothness and Stability in GANs](https://openreview.net/forum?id=HJeOekHKwr), Casey Chu, Kentaro Minami, Kenji Fukumizu

- [Kernel of CycleGAN as a Principal Homogeneous Space](https://openreview.net/forum?id=B1eWOJHKvB), Nikita Moriakov, Jonas Adler, Jonas Teuwen

- [U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation](https://openreview.net/forum?id=BJlZ5ySKPH), Junho Kim, Minjae Kim, Hyeonwoo Kang, Kwang Hee Lee

- [Understanding the Limitations of Conditional Generative Models](https://openreview.net/forum?id=r1lPleBFvH), Ethan Fetaya, Joern-Henrik Jacobsen, Will Grathwohl, Richard Zemel

- [Mixed-curvature Variational Autoencoders](https://openreview.net/forum?id=S1g6xeSKDS), Ondrej Skopek, Octavian-Eugen Ganea, Gary Bécigneul

- [Adversarial Lipschitz Regularization](https://openreview.net/forum?id=Bke_DertPB), Dávid Terjék

- [Consistency Regularization for Generative Adversarial Networks](https://openreview.net/forum?id=S1lxKlSKPH), Han Zhang, Zizhao Zhang, Augustus Odena, Honglak Lee

- [The Shape of Data: Intrinsic Distance for Data Distributions](https://openreview.net/forum?id=HyebplHYwB), Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Alex Bronstein, Ivan Oseledets, Emmanuel Mueller



## ICML 2020



- [Do GANs always have Nash equilibria?](https://proceedings.mlr.press/v119/farnia20a.html), Farzan Farnia, Asuman Ozdaglar

- [AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks](https://proceedings.mlr.press/v119/fu20b.html), Yonggan Fu, Wuyang Chen, Haotao Wang, Haoran Li, Yingyan Lin, Zhangyang Wang

- [SimGANs: Simulator-Based Generative Adversarial Networks for ECG Synthesis to Improve Deep ECG Classification](https://proceedings.mlr.press/v119/golany20a.html), omer Golany, Kira Radinsky, Daniel Freedman

- [SGD Learns One-Layer Networks in WGANs](https://proceedings.mlr.press/v119/lei20b.html), Qi Lei, Jason Lee, Alex Dimakis, Constantinos Daskalakis

- [InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs](https://proceedings.mlr.press/v119/lin20e.html), Zinan Lin, Kiran Thekumparampil, Giulia Fanti, Sewoong Oh

- [Semi-Supervised StyleGAN for Disentanglement Learning](https://proceedings.mlr.press/v119/nie20a.html), Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit Patel, Animashree Anandkumar

- [Implicit competitive regularization in GANs](https://proceedings.mlr.press/v119/schaefer20a.html), Florian Schaefer, Hongkai Zheng, Animashree Anandkumar

- [Small-GAN: Speeding up GAN Training using Core-Sets](https://proceedings.mlr.press/v119/sinha20b.html), Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena

- [Bridging the Gap Between f-GANs and Wasserstein GANs](https://proceedings.mlr.press/v119/song20a.html), Jiaming Song, Stefano Ermon

- [Learning disconnected manifolds: a no GAN’s land](https://proceedings.mlr.press/v119/tanielian20a.html), Ugo Tanielian, Thibaut Issenhuth, Elvis Dohmatob, Jeremie Mary

- [Unsupervised Discovery of Interpretable Directions in the GAN Latent Space](https://proceedings.mlr.press/v119/voynov20a.html), Andrey Voynov, Artem Babenko

- [Understanding and Stabilizing GANs’ Training Dynamics Using Control Theory](https://proceedings.mlr.press/v119/xu20d.html), Kun Xu, Chongxuan Li, Jun Zhu, Bo Zhang

- [On Leveraging Pretrained GANs for Generation with Limited Data](https://proceedings.mlr.press/v119/zhao20a.html), Miaoyun Zhao, Yulai Cong, Lawrence Carin

- [Feature Quantization Improves GAN Training](https://proceedings.mlr.press/v119/zhao20d.html), Yang Zhao, Chunyuan Li, Ping Yu, Jianfeng Gao, Changyou Chen

- [Invertible generative models for inverse problems: mitigating representation error and dataset bias](https://proceedings.mlr.press/v119/asim20a.html), Muhammad Asim, Max Daniels, Oscar Leong, Ali Ahmed, Paul Hand

- [VFlow: More Expressive Generative Flows with Variational Data Augmentation](https://proceedings.mlr.press/v119/chen20p.html), Jianfei Chen, Cheng Lu, Biqi Chenli, Jun Zhu, Tian Tian

- [Generative Pretraining From Pixels](https://proceedings.mlr.press/v119/chen20s.html), Mark Chen, Alec Radford, Rewon Child, Jeffrey Wu, Heewoo Jun, David Luan, Ilya Sutskever

- [Fair Generative Modeling via Weak Supervision](https://proceedings.mlr.press/v119/choi20a.html), Kristy Choi, Aditya Grover, Trisha Singh, Rui Shu, Stefano Ermon

- [Evaluating Lossy Compression Rates of Deep Generative Models](https://proceedings.mlr.press/v119/huang20c.html), Sicong Huang, Alireza Makhzani, Yanshuai Cao, Roger Grosse

- [Source Separation with Deep Generative Priors](https://proceedings.mlr.press/v119/jayaram20a.html), Vivek Jayaram, John Thickstun

- [Distribution Augmentation for Generative Modeling](https://proceedings.mlr.press/v119/jun20a.html), Heewoo Jun, Rewon Child, Mark Chen, John Schulman, Aditya Ramesh, Alec Radford, Ilya Sutskever

- [On the Power of Compressed Sensing with Generative Models](https://proceedings.mlr.press/v119/kamath20a.html), Akshay Kamath, Eric Price, Sushrut Karmalkar

- [Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities](https://proceedings.mlr.press/v119/kohler20a.html), Jonas Köhler, Leon Klein, Frank Noe

- [Reliable Fidelity and Diversity Metrics for Generative Models](https://proceedings.mlr.press/v119/naeem20a.html), Muhammad Ferjad Naeem, Seong Joon Oh, Youngjung Uh, Yunjey Choi, Jaejun Yoo

- [PolyGen: An Autoregressive Generative Model of 3D Meshes](https://proceedings.mlr.press/v119/nash20a.html), Charlie Nash, Yaroslav Ganin, S. M. Ali Eslami, Peter Battaglia

- [Implicit Generative Modeling for Efficient Exploration](https://proceedings.mlr.press/v119/ratzlaff20a.html), Neale Ratzlaff, Qinxun Bai, Li Fuxin, Wei Xu

- [Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data](https://proceedings.mlr.press/v119/such20a.html), Felipe Petroski Such, Aditya Rawal, Joel Lehman, Kenneth Stanley, Jeffrey Clune

- [Perceptual Generative Autoencoders](https://proceedings.mlr.press/v119/zhang20ab.html), Zijun Zhang, Ruixiang Zhang, Zongpeng Li, Yoshua Bengio, Liam Paull

- [Latent Bernoulli Autoencoder](https://proceedings.mlr.press/v119/fajtl20a.html), Jiri Fajtl, Vasileios Argyriou, Dorothy Monekosso, Paolo Remagnino

- [Variational Autoencoders with Riemannian Brownian Motion Priors](https://proceedings.mlr.press/v119/kalatzis20a.html), Dimitrios Kalatzis, David Eklund, Georgios Arvanitidis, Soren Hauberg

- [Topological Autoencoders](https://proceedings.mlr.press/v119/moor20a.html), Michael Moor, Max Horn, Bastian Rieck, Karsten Borgwardt

- [Eliminating the Invariance on the Loss Landscape of Linear Autoencoders](https://proceedings.mlr.press/v119/oftadeh20a.html), Reza Oftadeh, Jiayi Shen, Zhangyang Wang, Dylan Shell

- [ControlVAE: Controllable Variational Autoencoder](https://proceedings.mlr.press/v119/shao20b.html), Huajie Shao, Shuochao Yao, Dachun Sun, Aston Zhang, Shengzhong Liu, Dongxin Liu, Jun Wang, Tarek Abdelzaher

- [Learning Autoencoders with Relational Regularization](https://proceedings.mlr.press/v119/xu20e.html), Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin



## NeurIPS 2020



- [Teaching a GAN What Not to Learn](https://papers.nips.cc/paper/2020/hash/29405e2a4c22866a205f557559c7fa4b-Abstract.html), Siddarth Asokan, Chandra Seelamantula

- [Improving GAN Training with Probability Ratio Clipping and Sample Reweighting](https://papers.nips.cc/paper/2020/hash/3eb46aa5d93b7a5939616af91addfa88-Abstract.html), Yue Wu, Pan Zhou, Andrew G. Wilson, Eric Xing, Zhiting Hu

- [GramGAN: Deep 3D Texture Synthesis From 2D Exemplars](https://papers.nips.cc/paper/2020/hash/4df5bde009073d3ef60da64d736724d6-Abstract.html), Tiziano Portenier, Siavash Arjomand Bigdeli, Orcun Goksel

- [Differentiable Augmentation for Data-Efficient GAN Training](https://papers.nips.cc/paper/2020/hash/55479c55ebd1efd3ff125f1337100388-Abstract.html), Shengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, Song Han

- [COT-GAN: Generating Sequential Data via Causal Optimal Transport](https://papers.nips.cc/paper/2020/hash/641d77dd5271fca28764612a028d9c8e-Abstract.html), Tianlin Xu, Li Kevin Wenliang, Michael Munn, Beatrice Acciaio

- [GANSpace: Discovering Interpretable GAN Controls](https://papers.nips.cc/paper/2020/hash/6fe43269967adbb64ec6149852b5cc3e-Abstract.html), Erik Härkönen, Aaron Hertzmann, Jaakko Lehtinen, Sylvain Paris

- [Towards a Better Global Loss Landscape of GANs](https://papers.nips.cc/paper/2020/hash/738a6457be8432bab553e21b4235dd97-Abstract.html), Ruoyu Sun, Tiantian Fang, Alexander Schwing

- [Your GAN is Secretly an Energy-based Model and You Should Use Discriminator Driven Latent Sampling](https://papers.nips.cc/paper/2020/hash/90525e70b7842930586545c6f1c9310c-Abstract.html), Tong Che, Ruixiang ZHANG, Jascha Sohl-Dickstein, Hugo Larochelle, Liam Paull, Yuan Cao, Yoshua Bengio

- [GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators](https://papers.nips.cc/paper/2020/hash/9547ad6b651e2087bac67651aa92cd0d-Abstract.html), Dingfan Chen, Tribhuvanesh Orekondy, Mario Fritz

- [Reconstructing Perceptive Images from Brain Activity by Shape-Semantic GAN](https://papers.nips.cc/paper/2020/hash/9813b270ed0288e7c0388f0fd4ec68f5-Abstract.html), Tao Fang, Yu Qi, Gang Pan

- [Instance Selection for GANs](https://papers.nips.cc/paper/2020/hash/99f6a934a7cf277f2eaece8e3ce619b2-Abstract.html), Terrance DeVries, Michal Drozdzal, Graham W. Taylor

- [Top-k Training of GANs: Improving GAN Performance by Throwing Away Bad Samples](https://papers.nips.cc/paper/2020/hash/a851bd0d418b13310dd1e5e3ac7318ab-Abstract.html), Samarth Sinha, Zhengli Zhao, Anirudh Goyal ALIAS PARTH GOYAL, Colin A. Raffel, Augustus Odena

- [GAN Memory with No Forgetting](https://papers.nips.cc/paper/2020/hash/bf201d5407a6509fa536afc4b380577e-Abstract.html), Yulai Cong, Miaoyun Zhao, Jianqiao Li, Sijia Wang, Lawrence Carin

- [Hierarchical Patch VAE-GAN: Generating Diverse Videos from a Single Sample](https://papers.nips.cc/paper/2020/hash/c2f32522a84d5e6357e6abac087f1b0b-Abstract.html), Shir Gur, Sagie Benaim, Lior Wolf

- [HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis](https://papers.nips.cc/paper/2020/hash/c5d736809766d46260d816d8dbc9eb44-Abstract.html), Jungil Kong, Jaehyeon Kim, Jaekyoung Bae

- [Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Class-Imbalanced Data](https://papers.nips.cc/paper/2020/hash/d1e39c9bda5c80ac3d8ea9d658163967-Abstract.html), Utkarsh Ojha, Krishna Kumar Singh, Cho-Jui Hsieh, Yong Jae Lee

- [ColdGANs: Taming Language GANs with Cautious Sampling Strategies](https://papers.nips.cc/paper/2020/hash/db261d4f615f0e982983be499e57ccda-Abstract.html), Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier, Benjamin Piwowarski, Jacopo Staiano

- [CircleGAN: Generative Adversarial Learning across Spherical Circles](https://papers.nips.cc/paper/2020/hash/f14bc21be7eaeed046fed206a492e652-Abstract.html), Woohyeon Shim, Minsu Cho

- [ContraGAN: Contrastive Learning for Conditional Image Generation](https://papers.nips.cc/paper/2020/hash/f490c742cd8318b8ee6dca10af2a163f-Abstract.html), Minguk Kang, Jaesik Park

- [Sinkhorn Natural Gradient for Generative Models](https://papers.nips.cc/paper/2020/hash/122e27d57ae8ecb37f3f1da67abb33cb-Abstract.html), Zebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani

- [A Loss Function for Generative Neural Networks Based on Watson’s Perceptual Model](https://papers.nips.cc/paper/2020/hash/165a59f7cf3b5c4396ba65953d679f17-Abstract.html), Steffen Czolbe, Oswin Krause, Ingemar Cox, Christian Igel

- [Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance](https://papers.nips.cc/paper/2020/hash/1ac978c8020be6d7212aa71d4f040fc3-Abstract.html), Ziv Goldfeld, Kristjan Greenewald, Kengo Kato

- [Generative View Synthesis: From Single-view Semantics to Novel-view Images](https://papers.nips.cc/paper/2020/hash/3295c76acbf4caaed33c36b1b5fc2cb1-Abstract.html), Tewodros Amberbir Habtegebrial, Varun Jampani, Orazio Gallo, Didier Stricker

- [Training Generative Adversarial Networks by Solving Ordinary Differential Equations](https://papers.nips.cc/paper/2020/hash/3c8f9a173f749710d6377d3150cf90da-Abstract.html), Chongli Qin, Yan Wu, Jost Tobias Springenberg, Andy Brock, Jeff Donahue, Timothy Lillicrap, Pushmeet Kohli

- [Woodbury Transformations for Deep Generative Flows](https://papers.nips.cc/paper/2020/hash/3fb04953d95a94367bb133f862402bce-Abstract.html), You Lu, Bert Huang

- [Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence](https://papers.nips.cc/paper/2020/hash/43bb733c1b62a5e374c63cb22fa457b4-Abstract.html), Thomas Sutter, Imant Daunhawer, Julia Vogt

- [Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation](https://papers.nips.cc/paper/2020/hash/63c17d596f401acb520efe4a2a7a01ee-Abstract.html), Sajad Norouzi, David J. Fleet, Mohammad Norouzi

- [A Decentralized Parallel Algorithm for Training Generative Adversarial Nets](https://papers.nips.cc/paper/2020/hash/7e0a0209b929d097bd3e8ef30567a5c1-Abstract.html), Mingrui Liu, Wei Zhang, Youssef Mroueh, Xiaodong Cui, Jarret Ross, Tianbao Yang, Payel Das

- [Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining](https://papers.nips.cc/paper/2020/hash/81e3225c6ad49623167a4309eb4b2e75-Abstract.html), Austin Tripp, Erik Daxberger, José Miguel Hernández-Lobato

- [Training Generative Adversarial Networks with Limited Data](https://papers.nips.cc/paper/2020/hash/8d30aa96e72440759f74bd2306c1fa3d-Abstract.html), Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, Timo Aila

- [Improved Techniques for Training Score-Based Generative Models](https://papers.nips.cc/paper/2020/hash/92c3b916311a5517d9290576e3ea37ad-Abstract.html), Yang Song, Stefano Ermon

- [Robust Optimal Transport with Applications in Generative Modeling and Domain Adaptation](https://papers.nips.cc/paper/2020/hash/9719a00ed0c5709d80dfef33795dcef3-Abstract.html), Yogesh Balaji, Rama Chellappa, Soheil Feizi

- [DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation](https://papers.nips.cc/paper/2020/hash/bcf9d6bd14a2095866ce8c950b702341-Abstract.html), Alexandre Carlier, Martin Danelljan, Alexandre Alahi, Radu Timofte

- [Efficient Learning of Generative Models via Finite-Difference Score Matching](https://papers.nips.cc/paper/2020/hash/de6b1cf3fb0a3aa1244d30f7b8c29c41-Abstract.html), Tianyu Pang, Kun Xu, Chongxuan LI, Yang Song, Stefano Ermon, Jun Zhu

- [GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis](https://papers.nips.cc/paper/2020/hash/e92e1b476bb5262d793fd40931e0ed53-Abstract.html), Katja Schwarz, Yiyi Liao, Michael Niemeyer, Andreas Geiger

- [Learning Semantic-aware Normalization for Generative Adversarial Networks](https://papers.nips.cc/paper/2020/hash/f885a14eaf260d7d9f93c750e1174228-Abstract.html), Heliang Zheng, Jianlong Fu, Yanhong Zeng, Jiebo Luo, Zheng-Jun Zha

- [Goal-directed Generation of Discrete Structures with Conditional Generative Models](https://papers.nips.cc/paper/2020/hash/f9b9f0fef2274a6b7009b5d52f44a3b6-Abstract.html), Amina Mollaysa, Brooks Paige, Alexandros Kalousis

- [Lightweight Generative Adversarial Networks for Text-Guided Image Manipulation](https://papers.nips.cc/paper/2020/hash/fae0b27c451c728867a567e8c1bb4e53-Abstract.html), Bowen Li, Xiaojuan Qi, Philip Torr, Thomas Lukasiewicz

- [Hierarchical Quantized Autoencoders](https://papers.nips.cc/paper/2020/hash/309fee4e541e51de2e41f21bebb342aa-Abstract.html), Will Williams, Sam Ringer, Tom Ash, David MacLeod, Jamie Dougherty, John Hughes

- [Autoregressive Score Matching](https://papers.nips.cc/paper/2020/hash/4a4526b1ec301744aba9526d78fcb2a6-Abstract.html), Chenlin Meng, Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon

- [Implicit Rank-Minimizing Autoencoder](https://papers.nips.cc/paper/2020/hash/a9078e8653368c9c291ae2f8b74012e7-Abstract.html), Li Jing, Jure Zbontar, yann lecun

- [The Autoencoding Variational Autoencoder](https://papers.nips.cc/paper/2020/hash/ac10ff1941c540cd87c107330996f4f6-Abstract.html), Taylan Cemgil, Sumedh Ghaisas, Krishnamurthy Dvijotham, Sven Gowal, Pushmeet Kohli

- [Autoencoders that don't overfit towards the Identity](https://papers.nips.cc/paper/2020/hash/e33d974aae13e4d877477d51d8bafdc4-Abstract.html), Harald Steck

- [NVAE: A Deep Hierarchical Variational Autoencoder](https://papers.nips.cc/paper/2020/hash/e3b21256183cf7c2c7a66be163579d37-Abstract.html), Arash Vahdat, Jan Kautz

- [Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder](https://papers.nips.cc/paper/2020/hash/eddea82ad2755b24c4e168c5fc2ebd40-Abstract.html), Zhisheng Xiao, Qing Yan, Yali Amit

- [Compositional Visual Generation with Energy Based Models](https://papers.nips.cc/paper/2020/hash/49856ed476ad01fcff881d57e161d73f-Abstract.html), Yilun Du, Shuang Li, Igor Mordatch

- [Strictly Batch Imitation Learning by Energy-based Distribution Matching](https://papers.nips.cc/paper/2020/hash/524f141e189d2a00968c3d48cadd4159-Abstract.html), Daniel Jarrett, Ioana Bica, Mihaela van der Schaar

- [Bi-level Score Matching for Learning Energy-based Latent Variable Models](https://papers.nips.cc/paper/2020/hash/d25a34b9c2a87db380ecd7f7115882ec-Abstract.html), Fan Bao, Chongxuan LI, Kun Xu, Hang Su, Jun Zhu, Bo Zhang

- [Learning Latent Space Energy-Based Prior Model](https://papers.nips.cc/paper/2020/hash/fa3060edb66e6ff4507886f9912e1ab9-Abstract.html), Bo Pang, Tian Han, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu



## ICLR 2021



### Oral



- [Do 2D GANs Know 3D Shape? Unsupervised 3D Shape Reconstruction from 2D Image GANs](https://openreview.net/forum?id=FGqiDsBUKL0), Xingang Pan, Bo Dai, Ziwei Liu, Chen Change Loy, Ping Luo

- [Score-Based Generative Modeling through Stochastic Differential Equations](https://openreview.net/forum?id=PxTIG12RRHS), Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole

- [Image GANs meet Differentiable Rendering for Inverse Graphics and Interpretable 3D Neural Rendering](https://openreview.net/forum?id=yWkP7JuHX1), Yuxuan Zhang, Wenzheng Chen, Huan Ling, Jun Gao, Yinan Zhang, Antonio Torralba, Sanja Fidler

- [Improved Autoregressive Modeling with Distribution Smoothing](https://openreview.net/forum?id=rJA5Pz7lHKb), Chenlin Meng, Jiaming Song, Yang Song, Shengjia Zhao, Stefano Ermon



### Spotlight



- [VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models](https://openreview.net/forum?id=5m3SEczOV8L), Zhisheng Xiao, Karsten Kreis, Jan Kautz, Arash Vahdat

- [Large Scale Image Completion via Co-Modulated Generative Adversarial Networks](https://openreview.net/forum?id=sSjqmfsk95O), Shengyu Zhao, Jonathan Cui, Yilun Sheng, Yue Dong, Xiao Liang, Eric I-Chao Chang, Yan Xu

- [Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images](https://openreview.net/forum?id=RLRXCV6DbEJ), Rewon Child

- [A Good Image Generator Is What You Need for High-Resolution Video Synthesis](https://openreview.net/forum?id=6puCSjH3hwA), Yu Tian, Jian Ren, Menglei Chai, Kyle Olszewski, Xi Peng, Dimitris N. Metaxas, Sergey Tulyakov

- [GAN "Steerability" without optimization](https://openreview.net/forum?id=zDy_nQCXiIj), Nurit Spingarn, Ron Banner, Tomer Michaeli

- [Contrastive Divergence Learning is a Time Reversal Adversarial Game](https://openreview.net/forum?id=MLSvqIHRidA), Omer Yair, Tomer Michaeli

- [Influence Estimation for Generative Adversarial Networks](https://openreview.net/forum?id=opHLcXxYTC_), Naoyuki Terashita, Hiroki Ohashi, Yuichi Nonaka, Takashi Kanemaru

- [Distributional Sliced-Wasserstein and Applications to Generative Modeling](https://openreview.net/forum?id=QYjO70ACDK), Khai Nguyen, Nhat Ho, Tung Pham, Hung Bui

- [Disentangled Recurrent Wasserstein Autoencoder](https://openreview.net/forum?id=O7ms4LFdsX), Jun Han, Martin Renqiang Min, Ligong Han, Li Erran Li, Xuan Zhang

- [On Self-Supervised Image Representations for GAN Evaluation](https://openreview.net/forum?id=NeRdBeTionN), Stanislav Morozov, Andrey Voynov, Artem Babenko



### Poster



- [Training GANs with Stronger Augmentations via Contrastive Discriminator](https://openreview.net/forum?id=eo6U4CAwVmg), Jongheon Jeong, Jinwoo Shin

- [Enjoy Your Editing: Controllable GANs for Image Editing via Latent Space Navigation](https://openreview.net/forum?id=HOFxeCutxZR), Peiye Zhuang, Oluwasanmi O Koyejo, Alex Schwing

- [Using latent space regression to analyze and leverage compositionality in GANs](https://openreview.net/forum?id=sjuuTm4vj0), Lucy Chai, Jonas Wulff, Phillip Isola

- [GANs Can Play Lottery Tickets Too](https://openreview.net/forum?id=1AoMhc_9jER), Xuxi Chen, Zhenyu Zhang, Yongduo Sui, Tianlong Chen

- [CcGAN: Continuous Conditional Generative Adversarial Networks for Image Generation](https://openreview.net/forum?id=PrzjugOsDeE), Xin Ding, Yongwei Wang, Zuheng Xu, William J Welch, Z. Jane Wang

- [Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis](https://openreview.net/forum?id=1Fqg133qRaI), Bingchen Liu, Yizhe Zhu, Kunpeng Song, Ahmed Elgammal

- [DINO: A Conditional Energy-Based GAN for Domain Translation](https://openreview.net/forum?id=WAISmwsqDsb), Konstantinos Vougioukas, Stavros Petridis, Maja Pantic

- [Private Post-GAN Boosting](https://openreview.net/forum?id=6isfR3JCbi), Marcel Neunhoeffer, Steven Wu, Cynthia Dwork

- [GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy Images](https://openreview.net/forum?id=SHvF5xaueVn), Sungmin Cha, Taeeon Park, Byeongjoon Kim, Jongduk Baek, Taesup Moon

- [Taming GANs with Lookahead-Minmax](https://openreview.net/forum?id=ZW0yXJyNmoG), Tatjana Chavdarova, Matteo Pagliardini, Sebastian U Stich, François Fleuret, Martin Jaggi

- [Wasserstein-2 Generative Networks](https://openreview.net/forum?id=bEoxzW_EXsa), Alexander Korotin, Vage Egiazarian, Arip Asadulaev, Alexander Safin, Evgeny Burnaev

- [Learning Energy-Based Generative Models via Coarse-to-Fine Expanding and Sampling](https://openreview.net/forum?id=aD1_5zowqV), Yang Zhao, Jianwen Xie, Ping Li

- [Generative Time-series Modeling with Fourier Flows](https://openreview.net/forum?id=PpshD0AXfA), Ahmed Alaa, Alex James Chan, Mihaela van der Schaar

- [Conditional Generative Modeling via Learning the Latent Space](https://openreview.net/forum?id=VJnrYcnRc6), Sameera Ramasinghe, Kanchana Nisal Ranasinghe, Salman Khan, Nick Barnes, Stephen Gould

- [not-MIWAE: Deep Generative Modelling with Missing not at Random Data](https://openreview.net/forum?id=tu29GQT0JFy), Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen

- [Private Image Reconstruction from System Side Channels Using Generative Models](https://openreview.net/forum?id=y06VOYLcQXa), Yuanyuan Yuan, Shuai Wang, Junping Zhang

- [Counterfactual Generative Networks](https://openreview.net/forum?id=BXewfAYMmJw), Axel Sauer, Andreas Geiger

- [Learning to Generate 3D Shapes with Generative Cellular Automata](https://openreview.net/forum?id=rABUmU3ulQh), Dongsu Zhang, Changwoon Choi, Jeonghwan Kim, Young Min Kim

- [Reducing the Computational Cost of Deep Generative Models with Binary Neural Networks](https://openreview.net/forum?id=sTeoJiB4uR), Thomas Bird, Friso Kingma, David Barber

- [Group Equivariant Generative Adversarial Networks](https://openreview.net/forum?id=rgFNuJHHXv), Neel Dey, Antong Chen, Soheil Ghafurian

- [Refining Deep Generative Models via Discriminator Gradient Flow](https://openreview.net/forum?id=Zbc-ue9p_rE), Abdul Fatir Ansari, Ming Liang Ang, Harold Soh

- [Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling](https://openreview.net/forum?id=I4c4K9vBNny), Đorđe Miladinović, Aleksandar Stanić, Stefan Bauer, Jürgen Schmidhuber, Joachim M. Buhmann

- [Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models](https://openreview.net/forum?id=vhKe9UFbrJo), Yuge Shi, Brooks Paige, Philip Torr, Siddharth N

- [Unsupervised Meta-Learning through Latent-Space Interpolation in Generative Models](https://openreview.net/forum?id=XOjv2HxIF6i), Siavash Khodadadeh, Sharare Zehtabian, Saeed Vahidian, Weijia Wang, Bill Lin, Ladislau Boloni

- [Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesis](https://openreview.net/forum?id=Ig53hpHxS4), Rafael Valle, Kevin J. Shih, Ryan Prenger, Bryan Catanzaro

- [Understanding Over-parameterization in Generative Adversarial Networks](https://openreview.net/forum?id=C3qvk5IQIJY), Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi

- [Evaluating the Disentanglement of Deep Generative Models through Manifold Topology](https://openreview.net/forum?id=djwS0m4Ft_A), Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Y. Ng, Gunnar E. Carlsson, Stefano Ermon

- [Decentralized Attribution of Generative Models](https://openreview.net/forum?id=_kxlwvhOodK), Changhoon Kim, Yi Ren, Yezhou Yang

- [Bowtie Networks: Generative Modeling for Joint Few-Shot Recognition and Novel-View Synthesis](https://openreview.net/forum?id=ESG-DMKQKsD), Zhipeng Bao, Yu-Xiong Wang, Martial Hebert

- [A Geometric Analysis of Deep Generative Image Models and Its Applications](https://openreview.net/forum?id=GH7QRzUDdXG), Binxu Wang, Carlos R Ponce

- [Unsupervised Audiovisual Synthesis via Exemplar Autoencoders](https://openreview.net/forum?id=43VKWxg_Sqr), Kangle Deng, Aayush Bansal, Deva Ramanan

- [Property Controllable Variational Autoencoder via Invertible Mutual Dependence](https://openreview.net/forum?id=tYxG_OMs9WE), Xiaojie Guo, Yuanqi Du, Liang Zhao

- [Anytime Sampling for Autoregressive Models via Ordered Autoencoding](https://openreview.net/forum?id=TSRTzJnuEBS), Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, Stefano Ermon

- [Tomographic Auto-Encoder: Unsupervised Bayesian Recovery of Corrupted Data](https://openreview.net/forum?id=YtMG5ex0ou), Francesco Tonolini, Pablo Garcia Moreno, Andreas Damianou, Roderick Murray-Smith



## ICML 2021



- [Uncertainty Principles of Encoding GANs](https://proceedings.mlr.press/v139/feng21c.html), Ruili Feng, Zhouchen Lin, Jiapeng Zhu, Deli Zhao, Jingren Zhou, Zheng-Jun Zha

- [Understanding Noise Injection in GANs](https://proceedings.mlr.press/v139/feng21g.html), Ruili Feng, Deli Zhao, Zheng-Jun Zha

- [Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions](https://proceedings.mlr.press/v139/huster21a.html), Todd Huster, Jeremy Cohen, Zinan Lin, Kevin Chan, Charles Kamhoua, Nandi O. Leslie, Cho-Yu Jason Chiang, Vyas Sekar

- [Functional Space Analysis of Local GAN Convergence](https://proceedings.mlr.press/v139/khrulkov21a.html), Valentin Khrulkov, Artem Babenko, Ivan Oseledets

- [Neural SDEs as Infinite-Dimensional GANs](https://proceedings.mlr.press/v139/kidger21b.html), Patrick Kidger, James Foster, Xuechen Li, Terry J Lyons

- [WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points](https://proceedings.mlr.press/v139/no21a.html), Albert No, Taeho Yoon, Kwon Sehyun, Ernest K Ryu

- [On Characterizing GAN Convergence Through Proximal Duality Gap](https://proceedings.mlr.press/v139/sidheekh21a.html), Sahil Sidheekh, Aroof Aimen, Narayanan C Krishnan

- [Generative Adversarial Transformers](https://proceedings.mlr.press/v139/hudson21a.html), Drew A Hudson, Larry Zitnick

- [Provable Lipschitz Certification for Generative Models](https://proceedings.mlr.press/v139/jordan21a.html), Matt Jordan, Alex Dimakis

- [Prior Image-Constrained Reconstruction using Style-Based Generative Models](https://proceedings.mlr.press/v139/kelkar21a.html), Varun A Kelkar, Mark Anastasio

- [NeRF-VAE: A Geometry Aware 3D Scene Generative Model](https://proceedings.mlr.press/v139/kosiorek21a.html), Adam R Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Sona Mokra, Danilo Jimenez Rezende

- [Run-Sort-ReRun: Escaping Batch Size Limitations in Sliced Wasserstein Generative Models](https://proceedings.mlr.press/v139/lezama21a.html), Jose Lezama, Wei Chen, Qiang Qiu

- [Generative Adversarial Networks for Markovian Temporal Dynamics: Stochastic Continuous Data Generation](https://proceedings.mlr.press/v139/park21d.html), Sung Woo Park, Dong Wook Shu, Junseok Kwon

- [A Language for Counterfactual Generative Models](https://proceedings.mlr.press/v139/tavares21a.html), Zenna Tavares, James Koppel, Xin Zhang, Ria Das, Armando Solar-Lezama

- [Deep Generative Learning via Schrödinger Bridge](https://proceedings.mlr.press/v139/wang21l.html), Gefei Wang, Yuling Jiao, Qian Xu, Yang Wang, Can Yang

- [A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention](https://proceedings.mlr.press/v139/watanabe21a.html), Tomoki Watanabe, Paolo Favaro

- [Adversarial Purification with Score-based Generative Models](https://proceedings.mlr.press/v139/yoon21a.html), Jongmin Yoon, Sung Ju Hwang, Juho Lee

- [Understanding Failures in Out-of-Distribution Detection with Deep Generative Models](https://proceedings.mlr.press/v139/zhang21g.html), Lily Zhang, Mark Goldstein, Rajesh Ranganath

- [Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference](https://proceedings.mlr.press/v139/zhang21z.html), Shumao Zhang, Pengchuan Zhang, Thomas Y Hou

- [Unified Robust Semi-Supervised Variational Autoencoder](https://proceedings.mlr.press/v139/chen21a.html), Xu Chen

- [Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech](https://proceedings.mlr.press/v139/kim21f.html), Jaehyeon Kim, Jungil Kong, Juhee Son

- [MorphVAE: Generating Neural Morphologies from 3D-Walks using a Variational Autoencoder with Spherical Latent Space](https://proceedings.mlr.press/v139/laturnus21a.html), Sophie C. Laturnus, Philipp Berens

- [Autoencoder Image Interpolation by Shaping the Latent Space](https://proceedings.mlr.press/v139/oring21a.html), Alon Oring, Zohar Yakhini, Yacov Hel-Or

- [Spectral Smoothing Unveils Phase Transitions in Hierarchical Variational Autoencoders](https://proceedings.mlr.press/v139/pervez21a.html), Adeel Pervez, Efstratios Gavves

- [Autoencoding Under Normalization Constraints](https://proceedings.mlr.press/v139/yoon21c.html), Sangwoong Yoon, Yung-Kyun Noh, Frank Park

- [Learning from Nested Data with Ornstein Auto-Encoders](https://proceedings.mlr.press/v139/choi21a.html), Youngwon Choi, Sungdong Lee, Joong-Ho Won

- [Monte Carlo Variational Auto-Encoders](https://proceedings.mlr.press/v139/thin21a.html), Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov

- [Zero-Shot Text-to-Image Generation](https://proceedings.mlr.press/v139/ramesh21a.html), Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, Ilya Sutskever



## NeurIPS 2021 ([OpenReview](https://openreview.net/group?id=NeurIPS.cc/2021/Conference))



### Oral



- [Moser Flow: Divergence-based Generative Modeling on Manifolds](https://openreview.net/forum?id=qGvMv3undNJ), Noam Rozen, Aditya Grover, Maximilian Nickel, Yaron Lipman

- [Differentiable Quality Diversity](https://openreview.net/forum?id=uJGObgFU0lU), Matthew Christopher Fontaine, Stefanos Nikolaidis

- [Alias-Free Generative Adversarial Networks](https://openreview.net/forum?id=Owggnutk6lE), Tero Karras, Miika Aittala, Samuli Laine, Erik Härkönen, Janne Hellsten, Jaakko Lehtinen, Timo Aila



### Spotlight



- [Breaking the Dilemma of Medical Image-to-image Translation](https://openreview.net/forum?id=C0GmZH2RnVR), Lingke Kong, Chenyu Lian, Detian Huang, ZhenJiang Li, Yanle Hu, Qichao Zhou

- [Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling](https://openreview.net/forum?id=9BnCwiXB0ty), Valentin De Bortoli, James Thornton, Jeremy Heng, Arnaud Doucet

- [Statistical Regeneration Guarantees of the Wasserstein Autoencoder with Latent Space Consistency](https://openreview.net/forum?id=iFadi3f5V5I), Anish Chakrabarty, Swagatam Das

- [On the Value of Infinite Gradients in Variational Autoencoder Models](https://openreview.net/forum?id=oumDUrf2dAB), Bin Dai, Li Kevin Wenliang, David Wipf

- [Maximum Likelihood Training of Score-Based Diffusion Models](https://openreview.net/forum?id=AklttWFnxS9), Yang Song, Conor Durkan, Iain Murray, Stefano Ermon

- [A Variational Perspective on Diffusion-Based Generative Models and Score Matching](https://openreview.net/forum?id=bXehDYUjjXi), Chin-Wei Huang, Jae Hyun Lim, Aaron Courville

- [Diffusion Models Beat GANs on Image Synthesis](https://openreview.net/forum?id=OU98jZWS3x_), Prafulla Dhariwal, Alexander Quinn Nichol

- [Instance-Conditioned GAN](https://openreview.net/forum?id=aUuTEEcyY_), Arantxa Casanova, Marlene Careil, Jakob Verbeek, Michal Drozdzal, Adriana Romero



### Poster



- [Self-Supervised GANs with Label Augmentation](https://openreview.net/forum?id=MT0pTKLyzkT), Liang Hou, Huawei Shen, Qi Cao, Xueqi Cheng

- [Projected GANs Converge Faster](https://openreview.net/forum?id=fUxqIofPPi), Axel Sauer, Kashyap Chitta, Jens Müller, Andreas Geiger

- [Data-Efficient GAN Training Beyond (Just) Augmentations: A Lottery Ticket Perspective](https://openreview.net/forum?id=WQkGUUNsPu6), Tianlong Chen, Yu Cheng, Zhe Gan, Jingjing Liu, Zhangyang Wang

- [Invertible Tabular GANs: Killing Two Birds with One Stone for Tabular Data Synthesis](https://openreview.net/forum?id=tvDBe6K8L5o), JAEHOON LEE, Jihyeon Hyeong, Jinsung Jeon, Noseong Park, Jihoon Cho

- [Non-asymptotic Error Bounds for Bidirectional GANs](https://openreview.net/forum?id=Ifo8sa57U2f), Shiao Liu, Yunfei Yang, Jian Huang, Yuling Jiao, Yang Wang

- [Why Spectral Normalization Stabilizes GANs: Analysis and Improvements](https://openreview.net/forum?id=MLT9wFYMlJ9), Zinan Lin, Vyas Sekar, Giulia Fanti

- [CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks](https://openreview.net/forum?id=2r6F9duQ6o5), Sakshi Varshney, Vinay Kumar Verma, Srijith P K, Lawrence Carin, Piyush Rai

- [Self-Diagnosing GAN: Diagnosing Underrepresented Samples in Generative Adversarial Networks](https://openreview.net/forum?id=SGZn06ZXcG), Jinhee Lee, Haeri Kim, Youngkyu Hong, Hye Won Chung

- [Particle Cloud Generation with Message Passing Generative Adversarial Networks](https://openreview.net/forum?id=iorEu783qJ5), Raghav Kansal, Javier Duarte, Hao Su, Breno Orzari, Thiago R F P Tomei, Maurizio Pierini, Mary Touranakou, Jean-roch Vlimant, Dimitrios Gunopulos

- [TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up](https://openreview.net/forum?id=1GTpBZvNUrk), Yifan Jiang, Shiyu Chang, Zhangyang Wang

- [Low-Rank Subspaces in GANs](https://openreview.net/forum?id=Xp5BhDKdil5), Jiapeng Zhu, Ruili Feng, Yujun Shen, Deli Zhao, Zheng-Jun Zha, Jingren Zhou, Qifeng Chen

- [Lip to Speech Synthesis with Visual Context Attentional GAN](https://openreview.net/forum?id=x6z8J_17LP3), Minsu Kim, Joanna Hong, Yong Man Ro

- [Revisiting Discriminator in GAN Compression: A Generator-discriminator Cooperative Compression Scheme](https://openreview.net/forum?id=79xCSCP6qs), ShaoJie Li, Jie Wu, Xuefeng Xiao, Fei Chao, Xudong Mao, Rongrong Ji

- [EditGAN: High-Precision Semantic Image Editing](https://openreview.net/forum?id=ppv5yqhpNyE), Huan Ling, Karsten Kreis, Daiqing Li, Seung Wook Kim, Antonio Torralba, Sanja Fidler

- [Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training](https://openreview.net/forum?id=Ja-hVQrfeGZ), Minguk Kang, Woohyeon Joseph Shim, Minsu Cho, Jaesik Park

- [Rethinking Conditional GAN Training: An Approach using Geometrically Structured Latent Manifolds](https://openreview.net/forum?id=Hox8lKfr82L), Sameera Ramasinghe, Moshiur R Farazi, Salman Khan, Nick Barnes, Stephen Gould

- [BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation](https://openreview.net/forum?id=gISH-80g05u), Mingcong Liu, Qiang Li, Zekui Qin, Guoxin Zhang, Pengfei Wan, Wen Zheng

- [Data-Efficient Instance Generation from Instance Discrimination](https://openreview.net/forum?id=9BpjtPMyDQ), Ceyuan Yang, Yujun Shen, Yinghao Xu, Bolei Zhou

- [On the Frequency Bias of Generative Models](https://openreview.net/forum?id=IARK9TWiFRb), Katja Schwarz, Yiyi Liao, Andreas Geiger

- [Improved Transformer for High-Resolution GANs](https://openreview.net/forum?id=zmbiQmdtg9), Long Zhao, Zizhao Zhang, Ting Chen, Dimitris N. Metaxas, Han Zhang

- [Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data](https://openreview.net/forum?id=spjlJ4jeM_), Liming Jiang, Bo Dai, Wayne Wu, Chen Change Loy

- [Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN](https://openreview.net/forum?id=X8SLExrO2Lp), Zhenyu Xie, Zaiyu Huang, Fuwei Zhao, Haoye Dong, Michael Kampffmeyer, Xiaodan Liang

- [CogView: Mastering Text-to-Image Generation via Transformers](https://openreview.net/forum?id=cnWSyJNmeCE), Ming Ding, Zhuoyi Yang, Wenyi Hong, Wendi Zheng, Chang Zhou, Da Yin, Junyang Lin, Xu Zou, Zhou Shao, Hongxia Yang, Jie Tang

- [Improving Visual Quality of Image Synthesis by A Token-based Generator with Transformers](https://openreview.net/forum?id=lGoKo9WS2A_), Yanhong Zeng, Huan Yang, Hongyang Chao, Jianbo Wang, Jianlong Fu

- [Manifold Topology Divergence: a Framework for Comparing Data Manifolds](https://openreview.net/forum?id=Fj6kQJbHwM9), Serguei Barannikov, Ilya Trofimov, Grigorii Sotnikov, Ekaterina Trimbach, Alexander Korotin, Alexander Filippov, Evgeny Burnaev

- [DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks](https://openreview.net/forum?id=XN1M27T6uux), Boris van Breugel, Trent Kyono, Jeroen Berrevoets, Mihaela van der Schaar

- [A Unified View of cGANs with and without Classifiers](https://openreview.net/forum?id=j6KoGtzPYa), Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin

- [Conditional Generation Using Polynomial Expansions](https://openreview.net/forum?id=wPA_5Wsjt8i), Grigorios Chrysos, Markos Georgopoulos, Yannis Panagakis

- [Generative Occupancy Fields for 3D Surface-Aware Image Synthesis](https://openreview.net/forum?id=tHzvH4Rv1Qa), Xudong Xu, Xingang Pan, Dahua Lin, Bo Dai

- [Implicit Generative Copulas](https://openreview.net/forum?id=h1bPe7spQkr), Tim Janke, Mohamed Ghanmi, Florian Steinke

- [Don’t Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence](https://openreview.net/forum?id=waWmZSw0mn), Tianshi Cao, Alex Bie, Arash Vahdat, Sanja Fidler, Karsten Kreis

- [Learning Generative Vision Transformer with Energy-Based Latent Space for Saliency Prediction](https://openreview.net/forum?id=LoUdcqLuPej), Jing Zhang, Jianwen Xie, Nick Barnes, Ping Li

- [Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals](https://openreview.net/forum?id=Z_J5bCb4Rra), Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaid Harchaoui

- [On the Generative Utility of Cyclic Conditionals](https://openreview.net/forum?id=dPdrrr-YrgX), Chang Liu, Haoyue Tang, Tao Qin, Jintao Wang, Tie-Yan Liu

- [Score-based Generative Neural Networks for Large-Scale Optimal Transport](https://openreview.net/forum?id=PPzV1H4atM4), Max Daniels, Tyler Maunu, PAul HAnd

- [Bridging Explicit and Implicit Deep Generative Models via Neural Stein Estimators](https://openreview.net/forum?id=wHxnK7Ucogy), Qitian Wu, Rui Gao, Hongyuan Zha

- [On Memorization in Probabilistic Deep Generative Models](https://openreview.net/forum?id=PlGSgjFK2oJ), Gerrit J.J. Van den Burg, Chris Williams

- [Score-based Generative Modeling in Latent Space](https://openreview.net/forum?id=P9TYG0j-wtG), Arash Vahdat, Karsten Kreis, Jan Kautz

- [SketchGen: Generating Constrained CAD Sketches](https://openreview.net/forum?id=Oeb2LbHAfJ4), Wamiq Reyaz Para, Shariq Farooq Bhat, Paul Guerrero, Tom Kelly, Niloy Mitra, Leonidas Guibas, Peter Wonka

- [Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling](https://openreview.net/forum?id=0p0gt1Pn2Gv), Naoya Takeishi, Alexandros Kalousis

- [Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models](https://openreview.net/forum?id=rqjfa49ODLE), Phil Chen, Masha Itkina, Ransalu Senanayake, Mykel Kochenderfer

- [Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation](https://openreview.net/forum?id=Arn2E4IRjEB), Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio

- [Improving Robustness using Generated Data](https://openreview.net/forum?id=0NXUSlb6oEu), Sven Gowal, Sylvestre-Alvise Rebuffi, Olivia Wiles, Florian Stimberg, Dan Andrei Calian, Timothy Mann

- [D2C: Diffusion-Decoding Models for Few-Shot Conditional Generation](https://openreview.net/forum?id=4vUZPUKZsr5), Abhishek Sinha, Jiaming Song, Chenlin Meng, Stefano Ermon

- [Shape your Space: A Gaussian Mixture Regularization Approach to Deterministic Autoencoders](https://openreview.net/forum?id=WybjTtCKfGi), Amrutha Saseendran, Kathrin Skubch, Stefan Falkner, Margret Keuper

- [On Density Estimation with Diffusion Models](https://openreview.net/forum?id=2LdBqxc1Yv), Diederik P Kingma, Tim Salimans, Ben Poole, Jonathan Ho

- [Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections](https://openreview.net/forum?id=oa1AMhWKrS), Kimia Nadjahi, Alain Durmus, Pierre Jacob, Roland Badeau, Umut Simsekli

- [PortaSpeech: Portable and High-Quality Generative Text-to-Speech](https://openreview.net/forum?id=xmJsuh8xlq), Yi Ren, Jinglin Liu, Zhou Zhao

- [Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models](https://openreview.net/forum?id=-nLW4nhdkO), Keunseo Kim, JunCheol Shin, Heeyoung Kim

- [Topographic VAEs learn Equivariant Capsules](https://openreview.net/forum?id=AVWROGUWpu), T. Anderson Keller, Max Welling

- [ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE](https://openreview.net/forum?id=SBiKnJW9fy), Qingzhong Ai, LIRONG HE, SHIYU LIU, Zenglin Xu

- [Understanding Instance-based Interpretability of Variational Auto-Encoders](https://openreview.net/forum?id=a5-37ER8qTI), Zhifeng Kong, Kamalika Chaudhuri

- [Local Disentanglement in Variational Auto-Encoders Using Jacobian $L_1$ Regularization](https://openreview.net/forum?id=8xyNqPvFZwC), Travers Rhodes, Daniel Lee

- [Consistency Regularization for Variational Auto-Encoders](https://openreview.net/forum?id=djbC2A4uTHP), Samarth Sinha, Adji Bousso Dieng