77 Results

Poster
Tue 7:00 Evaluating Lossy Compression Rates of Deep Generative Models
Sicong Huang, Alireza Makhzani, Yanshuai Cao, Roger Grosse
Poster
Tue 7:00 Improving Generative Imagination in Object-Centric World Models
Zhixuan Lin, Yi-Fu Wu, Skand Peri, Bofeng Fu, Jindong Jiang, Sungjin Ahn
Poster
Tue 7:00 Generative Flows with Matrix Exponential
Changyi Xiao, Ligang Liu
Poster
Tue 7:00 On Implicit Regularization in $\beta$-VAEs
Abhishek Kumar, Ben Poole
Poster
Tue 7:00 Recurrent Hierarchical Topic-Guided RNN for Language Generation
Dandan Guo, Bo Chen, Ruiying Lu, Mingyuan Zhou
Poster
Tue 7:00 ControlVAE: Controllable Variational Autoencoder
Huajie Shao, Shuochao Yao, Dachun Sun, Aston Zhang, Shengzhong Liu, Dongxin Liu, Jun Wang, Tarek Abdelzaher
Poster
Tue 7:00 All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference
Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan
Poster
Tue 7:00 Amortized Population Gibbs Samplers with Neural Sufficient Statistics
Hao Wu, Heiko Zimmermann, Eli Sennesh, Tuan Anh Le, Jan-Willem van de Meent
Poster
Tue 7:00 Learning from Irregularly-Sampled Time Series: A Missing Data Perspective
Steve Li, Benjamin M Marlin
Poster
Tue 7:00 Fair Generative Modeling via Weak Supervision
Kristy Choi, Aditya Grover, Trisha Singh, Rui Shu, Stefano Ermon
Poster
Tue 7:00 Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling
Will Grathwohl, Kuan-Chieh Wang, Jörn Jacobsen, David Duvenaud, Richard Zemel
Poster
Tue 9:00 A Chance-Constrained Generative Framework for Sequence Optimization
Xianggen Liu, Qiang Liu, Sen Song , Jian Peng
Poster
Tue 9:00 Source Separation with Deep Generative Priors
Vivek Jayaram, John Thickstun
Poster
Tue 9:00 Feature Quantization Improves GAN Training
Yang Zhao, Chunyuan Li, Iris Yu, Jianfeng Gao, Changyou Chen
Poster
Tue 9:00 Variable Skipping for Autoregressive Range Density Estimation
Eric Liang, Zongheng Yang, Ion Stoica, Pieter Abbeel, Yan Duan, Peter Chen
Poster
Tue 9:00 Scalable Deep Generative Modeling for Sparse Graphs
Hanjun Dai, Azade Nazi, Yujia Li, Bo Dai, Dale Schuurmans
Poster
Tue 10:00 Generative Pretraining From Pixels
Mark Chen, Alec Radford, Rewon Child, Jeffrey K Wu, Heewoo Jun, David Luan, Ilya Sutskever
Poster
Tue 10:00 Learning To Stop While Learning To Predict
Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song
Poster
Tue 10:00 Training Deep Energy-Based Models with f-Divergence Minimization
Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon
Poster
Tue 12:00 Normalizing Flows on Tori and Spheres
Danilo J. Rezende, George Papamakarios, Sebastien Racaniere, Michael Albergo, Gurtej Kanwar, Phiala Shanahan, Kyle Cranmer
Poster
Tue 12:00 Weakly-Supervised Disentanglement Without Compromises
Francesco Locatello, Ben Poole, Gunnar Ratsch, Bernhard Schölkopf, Olivier Bachem, Michael Tschannen
Poster
Tue 12:00 SimGANs: Simulator-Based Generative Adversarial Networks for ECG Synthesis to Improve Deep ECG Classification
Tomer Golany, Kira Radinsky, Daniel Freedman
Poster
Tue 12:00 On Contrastive Learning for Likelihood-free Inference
Conor Durkan, Iain Murray, George Papamakarios
Poster
Tue 13:00 Predictive Sampling with Forecasting Autoregressive Models
Auke Wiggers, Emiel Hoogeboom
Poster
Tue 13:00 Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities
Jonas Köhler, Leon Klein, Frank Noe
Poster
Tue 14:00 Improving Molecular Design by Stochastic Iterative Target Augmentation
Kevin Yang, Wengong Jin, Kyle Swanson, Regina Barzilay, Tommi Jaakkola
Poster
Tue 15:00 Unsupervised Speech Decomposition via Triple Information Bottleneck
Kaizhi Qian, Yang Zhang, Shiyu Chang, Mark Hasegawa-Johnson, David Cox
Poster
Tue 18:00 Rate-distortion optimization guided autoencoder for isometric embedding in Euclidean latent space
Keizo Kato, Jing Zhou, Tomotake Sasaki, Akira Nakagawa
Poster
Wed 5:00 Hierarchical Generation of Molecular Graphs using Structural Motifs
Wengong Jin, Regina Barzilay, Tommi Jaakkola
Poster
Wed 5:00 VFlow: More Expressive Generative Flows with Variational Data Augmentation
Jianfei Chen, Cheng Lu, Biqi Chenli, Jun Zhu, Tian Tian
Poster
Wed 8:00 InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs
Zinan Lin, Kiran Thekumparampil, Giulia Fanti, Sewoong Oh
Poster
Wed 8:00 Optimal transport mapping via input convex neural networks
Ashok Makkuva, Amir Taghvaei, Sewoong Oh, Jason Lee
Poster
Wed 8:00 Undirected Graphical Models as Approximate Posteriors
Arash Vahdat, Evgeny Andriyash, William Macready
Poster
Wed 8:00 The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
Bin Dai, Ziyu Wang, David Wipf
Poster
Wed 10:00 Hypernetwork approach to generating point clouds
Przemysław Spurek, Sebastian Winczowski, Jacek Tabor, Maciej Zamorski, Maciej Zieba, Tomasz Trzcinski
Poster
Wed 10:00 Small-GAN: Speeding up GAN Training using Core-Sets
Samrath Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena
Poster
Wed 10:00 Learning Calibratable Policies using Programmatic Style-Consistency
Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew Hausknecht
Poster
Wed 11:00 Multilinear Latent Conditioning for Generating Unseen Attribute Combinations
Markos Georgopoulos, Grigorios Chrysos, Maja Pantic, Yannis Panagakis
Poster
Wed 11:00 Deep Gaussian Markov Random Fields
Per Sidén, Fredrik Lindsten
Poster
Wed 11:00 PolyGen: An Autoregressive Generative Model of 3D Meshes
Charlie Nash, Yaroslav Ganin, S. M. Ali Eslami, Peter Battaglia
Poster
Wed 12:00 Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables
Q. Wang, Herke van Hoof
Poster
Wed 12:00 Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows
Rob Cornish, Anthony Caterini, George Deligiannidis, Arnaud Doucet
Poster
Wed 16:00 On Relativistic f-Divergences
Alexia Jolicoeur-Martineau
Poster
Thu 6:00 Calibration, Entropy Rates, and Memory in Language Models
Mark Braverman, Xinyi Chen, Sham Kakade, Karthik Narasimhan, Cyril Zhang, Yi Zhang
Poster
Thu 6:00 On Breaking Deep Generative Model-based Defenses and Beyond
Yanzhi Chen, Renjie Xie, Zhanxing Zhu
Poster
Thu 6:00 Tails of Lipschitz Triangular Flows
Priyank Jaini, Ivan Kobyzev, Yaoliang Yu, Marcus Brubaker
Poster
Thu 6:00 Robustifying Sequential Neural Processes
Jaesik Yoon, Gautam Singh, Sungjin Ahn
Poster
Thu 6:00 Bridging the Gap Between f-GANs and Wasserstein GANs
Jiaming Song, Stefano Ermon
Poster
Thu 6:00 GraphOpt: Learning Optimization Models of Graph Formation
Rakshit Trivedi, Jiachen Yang, Hongyuan Zha
Poster
Thu 6:00 Latent Variable Modelling with Hyperbolic Normalizing Flows
Joey Bose, Ariella Smofsky, Renjie Liao, Prakash Panangaden, Will Hamilton
Poster
Thu 7:00 Semi-Supervised StyleGAN for Disentanglement Learning
Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit Patel, Anima Anandkumar
Poster
Thu 7:00 ACFlow: Flow Models for Arbitrary Conditional Likelihoods
Yang Li, Shoaib Akbar, Junier Oliva
Poster
Thu 7:00 Multi-Objective Molecule Generation using Interpretable Substructures
Wengong Jin, Regina Barzilay, Tommi Jaakkola
Poster
Thu 7:00 Semi-Supervised Learning with Normalizing Flows
Pavel Izmailov, Polina Kirichenko, Marc Finzi, Andrew Wilson
Poster
Thu 7:00 Understanding and Stabilizing GANs' Training Dynamics Using Control Theory
Taufik Xu, Chongxuan Li, Jun Zhu, Bo Zhang
Poster
Thu 7:00 Educating Text Autoencoders: Latent Representation Guidance via Denoising
Tianxiao Shen, Jonas Mueller, Regina Barzilay, Tommi Jaakkola
Poster
Thu 7:00 Distribution Augmentation for Generative Modeling
Heewoo Jun, Rewon Child, Mark Chen, John Schulman, Aditya Ramesh, Alec Radford, Ilya Sutskever
Poster
Thu 7:00 Perceptual Generative Autoencoders
Zijun Zhang, Ruixiang ZHANG, Zongpeng Li, Yoshua Bengio, Liam Paull
Poster
Thu 9:00 Energy-Based Processes for Exchangeable Data
Mengjiao Yang, Bo Dai, Hanjun Dai, Dale Schuurmans
Poster
Thu 9:00 WaveFlow: A Compact Flow-based Model for Raw Audio
Wei Ping, Kainan Peng, Kexin Zhao, Zhao Song
Poster
Thu 9:00 Unsupervised Discovery of Interpretable Directions in the GAN Latent Space
Andrey Voynov, Artem Babenko
Poster
Thu 12:00 Predictive Coding for Locally-Linear Control
Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung Bui
Poster
Thu 12:00 Learning Flat Latent Manifolds with VAEs
Nutan Chen, Alexej Klushyn, Francesco Ferroni, Justin Bayer, Patrick van der Smagt
Poster
Thu 12:00 Low Bias Low Variance Gradient Estimates for Hierarchical Boolean Stochastic Networks
Adeel Pervez, Taco Cohen, Stratis Gavves
Poster
Thu 13:00 Stochastic Latent Residual Video Prediction
Jean-Yves Franceschi, Edouard Delasalles, Mickael Chen, Sylvain Lamprier, Patrick Gallinari
Poster
Thu 13:00 Latent Bernoulli Autoencoder
Jiri Fajtl, Vasileios Argyriou, Dorothy Monekosso, Paolo Remagnino
Poster
Thu 13:00 A Generative Model for Molecular Distance Geometry
Gregor Simm, Jose Miguel Hernandez-Lobato
Poster
Thu 14:00 The continuous categorical: a novel simplex-valued exponential family
Elliott Gordon-Rodriguez, Gabriel Loaiza-Ganem, John Cunningham
Poster
Thu 14:00 Variational Autoencoders with Riemannian Brownian Motion Priors
Dimitris Kalatzis, David Eklund, Georgios Arvanitidis, Søren Hauberg
Poster
Thu 15:00 Reliable Fidelity and Diversity Metrics for Generative Models
Ferjad Naeem, Seong Joon Oh, Yunjey Choi, Youngjung Uh, Jaejun Yoo
Poster
Thu 17:00 On the Power of Compressed Sensing with Generative Models
Akshay Kamath, Eric Price, Sushrut Karmalkar
Poster
Thu 17:00 A Graph to Graphs Framework for Retrosynthesis Prediction
Chence Shi, Minkai Xu, Hongyu Guo, Ming Zhang, Jian Tang
Poster
Thu 17:00 Learning Autoencoders with Relational Regularization
Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin
Workshop
Fri 0:30 Invited Talk 2: Bolei Zhou - Interpreting and Leveraging the Latent Semantics in Deep Generative Models
Wojciech Samek
Workshop
Fri 2:00 Poster session 1
Workshop
Sat 4:10 Invited talk 2: Detecting Distribution Shift with Deep Generative Models
Eric Nalisnick
Workshop
Sat 7:15 "Latent Space Optimization with Deep Generative Models"
Jose Miguel Hernandez-Lobato