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Poster
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Tue 7:00 |
ControlVAE: Controllable Variational Autoencoder Huajie Shao, Shuochao Yao, Dachun Sun, Aston Zhang, Shengzhong Liu, Dongxin Liu, Jun Wang, Tarek Abdelzaher |
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Poster
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Tue 7:00 |
On Implicit Regularization in $\beta$-VAEs Abhishek Kumar, Ben Poole |
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Poster
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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 |
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Poster
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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 |
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Poster
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Tue 7:00 |
Fair Generative Modeling via Weak Supervision Kristy Choi, Aditya Grover, Trisha Singh, Rui Shu, Stefano Ermon |
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Poster
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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 |
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Poster
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Tue 7:00 |
Evaluating Lossy Compression Rates of Deep Generative Models Sicong Huang, Alireza Makhzani, Yanshuai Cao, Roger Grosse |
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Poster
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Tue 7:00 |
Improving Generative Imagination in Object-Centric World Models Zhixuan Lin, Yi-Fu Wu, Skand Peri, Bofeng Fu, Jindong Jiang, Sungjin Ahn |
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Poster
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Tue 7:00 |
Generative Flows with Matrix Exponential Changyi Xiao, Ligang Liu |
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Poster
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Tue 7:00 |
Learning from Irregularly-Sampled Time Series: A Missing Data Perspective Steve Li, Benjamin M Marlin |
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Poster
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Tue 7:00 |
Recurrent Hierarchical Topic-Guided RNN for Language Generation Dandan Guo, Bo Chen, Ruiying Lu, Mingyuan Zhou |
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Poster
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Tue 8:00 |
Near-optimal sample complexity bounds for learning Latent $k-$polytopes and applications to Ad-Mixtures Chiru Bhattacharyya, Ravindran Kannan |
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Poster
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Tue 8:00 |
Associative Memory in Iterated Overparameterized Sigmoid Autoencoders Yibo Jiang, Cengiz Pehlevan |
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Poster
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Tue 9:00 |
Feature Quantization Improves GAN Training Yang Zhao, Chunyuan Li, Iris Yu, Jianfeng Gao, Changyou Chen |
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Poster
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Tue 9:00 |
A Chance-Constrained Generative Framework for Sequence Optimization Xianggen Liu, Qiang Liu, Sen Song , Jian Peng |
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Poster
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Tue 9:00 |
Source Separation with Deep Generative Priors Vivek Jayaram, John Thickstun |
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Poster
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Tue 9:00 |
Scalable Deep Generative Modeling for Sparse Graphs Hanjun Dai, Azade Nazi, Yujia Li, Bo Dai, Dale Schuurmans |
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Poster
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Tue 9:00 |
Variable Skipping for Autoregressive Range Density Estimation Eric Liang, Zongheng Yang, Ion Stoica, Pieter Abbeel, Yan Duan, Peter Chen |
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Poster
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Tue 10:00 |
Learning To Stop While Learning To Predict Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song |
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Poster
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Tue 10:00 |
Training Deep Energy-Based Models with f-Divergence Minimization Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon |
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Poster
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Tue 10:00 |
Generative Pretraining From Pixels Mark Chen, Alec Radford, Rewon Child, Jeffrey K Wu, Heewoo Jun, David Luan, Ilya Sutskever |
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Poster
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Tue 10:00 |
Incremental Sampling Without Replacement for Sequence Models Kensen Shi, David Bieber, Charles Sutton |
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Poster
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Tue 12:00 |
On Contrastive Learning for Likelihood-free Inference Conor Durkan, Iain Murray, George Papamakarios |
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Poster
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Tue 12:00 |
Normalizing Flows on Tori and Spheres Danilo J. Rezende, George Papamakarios, Sebastien Racaniere, Michael Albergo, Gurtej Kanwar, Phiala Shanahan, Kyle Cranmer |
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Poster
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Tue 12:00 |
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello, Ben Poole, Gunnar Ratsch, Bernhard Schölkopf, Olivier Bachem, Michael Tschannen |
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Poster
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Tue 12:00 |
SimGANs: Simulator-Based Generative Adversarial Networks for ECG Synthesis to Improve Deep ECG Classification Tomer Golany, Kira Radinsky, Daniel Freedman |
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Poster
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Tue 13:00 |
Predictive Sampling with Forecasting Autoregressive Models Auke Wiggers, Emiel Hoogeboom |
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Poster
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Tue 13:00 |
Latent Space Factorisation and Manipulation via Matrix Subspace Projection Xiao Li, Chenghua Lin, Ruizhe Li, Chaozheng Wang, Frank Guerin |
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Poster
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Tue 13:00 |
Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities Jonas Köhler, Leon Klein, Frank Noe |
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Poster
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Tue 14:00 |
Improving Molecular Design by Stochastic Iterative Target Augmentation Kevin Yang, Wengong Jin, Kyle Swanson, Regina Barzilay, Tommi Jaakkola |
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Poster
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Tue 15:00 |
Unsupervised Speech Decomposition via Triple Information Bottleneck Kaizhi Qian, Yang Zhang, Shiyu Chang, Mark Hasegawa-Johnson, David Cox |
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Poster
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Tue 15:00 |
Invertible generative models for inverse problems: mitigating representation error and dataset bias Muhammad Asim, Max Daniels, Oscar Leong, Ali Ahmed, Paul Hand |
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Poster
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Tue 18:00 |
Rate-distortion optimization guided autoencoder for isometric embedding in Euclidean latent space Keizo Kato, Jing Zhou, Tomotake Sasaki, Akira Nakagawa |
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Poster
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Wed 5:00 |
VFlow: More Expressive Generative Flows with Variational Data Augmentation Jianfei Chen, Cheng Lu, Biqi Chenli, Jun Zhu, Tian Tian |
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Poster
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Wed 5:00 |
Learning Structured Latent Factors from Dependent Data:A Generative Model Framework from Information-Theoretic Perspective Ruixiang ZHANG, Masanori Koyama, Katsuhiko Ishiguro |
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Poster
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Wed 5:00 |
Hierarchical Generation of Molecular Graphs using Structural Motifs Wengong Jin, Regina Barzilay, Tommi Jaakkola |
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Poster
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Wed 5:00 |
Convolutional dictionary learning based auto-encoders for natural exponential-family distributions Bahareh Tolooshams, Andrew Song, Simona Temereanca, Demba Ba |
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Poster
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Wed 8:00 |
Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck |
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Poster
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Wed 8:00 |
Undirected Graphical Models as Approximate Posteriors Arash Vahdat, Evgeny Andriyash, William Macready |
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Poster
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Wed 8:00 |
InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs Zinan Lin, Kiran Thekumparampil, Giulia Fanti, Sewoong Oh |
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Poster
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Wed 8:00 |
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse Bin Dai, Ziyu Wang, David Wipf |
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Poster
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Wed 8:00 |
Sample Amplification: Increasing Dataset Size even when Learning is Impossible Brian Axelrod, Shivam Garg, Vatsal Sharan, Gregory Valiant |
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Poster
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Wed 8:00 |
Optimal transport mapping via input convex neural networks Ashok Makkuva, Amir Taghvaei, Sewoong Oh, Jason Lee |
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Poster
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Wed 10:00 |
Learning Calibratable Policies using Programmatic Style-Consistency Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew Hausknecht |
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Poster
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Wed 10:00 |
Hypernetwork approach to generating point clouds Przemysław Spurek, Sebastian Winczowski, Jacek Tabor, Maciej Zamorski, Maciej Zieba, Tomasz Trzcinski |
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Poster
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Wed 10:00 |
Small-GAN: Speeding up GAN Training using Core-Sets Samrath Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena |
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Poster
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Wed 11:00 |
PolyGen: An Autoregressive Generative Model of 3D Meshes Charlie Nash, Yaroslav Ganin, S. M. Ali Eslami, Peter Battaglia |
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Poster
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Wed 11:00 |
Deep Gaussian Markov Random Fields Per Sidén, Fredrik Lindsten |
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Poster
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Wed 11:00 |
Multilinear Latent Conditioning for Generating Unseen Attribute Combinations Markos Georgopoulos, Grigorios Chrysos, Maja Pantic, Yannis Panagakis |
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Poster
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Wed 12:00 |
Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows Rob Cornish, Anthony Caterini, George Deligiannidis, Arnaud Doucet |
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Poster
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Wed 12:00 |
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani |
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Poster
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Wed 12:00 |
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables Q. Wang, Herke van Hoof |
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Poster
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Wed 13:00 |
Continuous Time Bayesian Networks with Clocks Nicolai Engelmann, Dominik Linzner, Heinz Koeppl |
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Poster
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Wed 16:00 |
On Relativistic f-Divergences Alexia Jolicoeur-Martineau |
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Poster
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Wed 16:00 |
Spread Divergence Mingtian Zhang, Peter Hayes, Thomas Bird, Raza Habib, David Barber |
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Poster
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Thu 6:00 |
Causal Inference using Gaussian Processes with Structured Latent Confounders Sam Witty, Kenta Takatsu, David Jensen, Vikash Mansinghka |
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Poster
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Thu 6:00 |
Bridging the Gap Between f-GANs and Wasserstein GANs Jiaming Song, Stefano Ermon |
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Poster
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Thu 6:00 |
How to Train Your Neural ODE: the World of Jacobian and Kinetic Regularization Chris Finlay, Jörn Jacobsen, Levon Nurbekyan, Adam Oberman |
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Poster
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Thu 6:00 |
On Breaking Deep Generative Model-based Defenses and Beyond Yanzhi Chen, Renjie Xie, Zhanxing Zhu |
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Poster
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Thu 6:00 |
GraphOpt: Learning Optimization Models of Graph Formation Rakshit Trivedi, Jiachen Yang, Hongyuan Zha |
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Poster
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Thu 6:00 |
Robustifying Sequential Neural Processes Jaesik Yoon, Gautam Singh, Sungjin Ahn |
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Poster
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Thu 6:00 |
Calibration, Entropy Rates, and Memory in Language Models Mark Braverman, Xinyi Chen, Sham Kakade, Karthik Narasimhan, Cyril Zhang, Yi Zhang |
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Poster
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Thu 6:00 |
Tails of Lipschitz Triangular Flows Priyank Jaini, Ivan Kobyzev, Yaoliang Yu, Marcus Brubaker |
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Poster
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Thu 6:00 |
Latent Variable Modelling with Hyperbolic Normalizing Flows Joey Bose, Ariella Smofsky, Renjie Liao, Prakash Panangaden, Will Hamilton |
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Poster
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Thu 7:00 |
Semi-Supervised Learning with Normalizing Flows Pavel Izmailov, Polina Kirichenko, Marc Finzi, Andrew Wilson |
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Poster
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Thu 7:00 |
ACFlow: Flow Models for Arbitrary Conditional Likelihoods Yang Li, Shoaib Akbar, Junier Oliva |
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Poster
|
Thu 7:00 |
Multi-Objective Molecule Generation using Interpretable Substructures Wengong Jin, Regina Barzilay, Tommi Jaakkola |
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Poster
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Thu 7:00 |
Semi-Supervised StyleGAN for Disentanglement Learning Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit Patel, Anima Anandkumar |
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Poster
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Thu 7:00 |
Learning Task-Agnostic Embedding of Multiple Black-Box Experts for Multi-Task Model Fusion Nghia Hoang, Thanh Lam, Bryan Kian Hsiang Low, Patrick Jaillet |
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Poster
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Thu 7:00 |
Fractal Gaussian Networks: A sparse random graph model based on Gaussian Multiplicative Chaos Subhroshekhar Ghosh, Krishna Balasubramanian, Xiaochuan Yang |
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Poster
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Thu 7:00 |
Variational Inference for Sequential Data with Future Likelihood Estimates Geon-Hyeong Kim, Baezii RL, Hongseok Yang, Kee-Eung Kim |
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Poster
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Thu 7:00 |
Understanding and Stabilizing GANs' Training Dynamics Using Control Theory Taufik Xu, Chongxuan Li, Jun Zhu, Bo Zhang |
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Poster
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Thu 7:00 |
Educating Text Autoencoders: Latent Representation Guidance via Denoising Tianxiao Shen, Jonas Mueller, Regina Barzilay, Tommi Jaakkola |
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Poster
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Thu 7:00 |
Time-aware Large Kernel Convolutions Vasileios Lioutas, Yuhong Guo |
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Poster
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Thu 7:00 |
Perceptual Generative Autoencoders Zijun Zhang, Ruixiang ZHANG, Zongpeng Li, Yoshua Bengio, Liam Paull |
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Poster
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Thu 7:00 |
Distribution Augmentation for Generative Modeling Heewoo Jun, Rewon Child, Mark Chen, John Schulman, Aditya Ramesh, Alec Radford, Ilya Sutskever |
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Poster
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Thu 8:00 |
SGD Learns One-Layer Networks in WGANs Qi Lei, Jason Lee, Alex Dimakis, Constantinos Daskalakis |
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Poster
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Thu 8:00 |
Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems Zhe Dong, Bryan Seybold, Kevin Murphy, Hung Bui |
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Poster
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Thu 8:00 |
AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation Jae Hyun Lim, Aaron Courville, Christopher Pal, Chin-Wei Huang |
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Poster
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Thu 9:00 |
WaveFlow: A Compact Flow-based Model for Raw Audio Wei Ping, Kainan Peng, Kexin Zhao, Zhao Song |
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Poster
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Thu 9:00 |
Unsupervised Discovery of Interpretable Directions in the GAN Latent Space Andrey Voynov, Artem Babenko |
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Poster
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Thu 9:00 |
Energy-Based Processes for Exchangeable Data Mengjiao Yang, Bo Dai, Hanjun Dai, Dale Schuurmans |
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Poster
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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 |
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Poster
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Thu 12:00 |
Learning Flat Latent Manifolds with VAEs Nutan Chen, Alexej Klushyn, Francesco Ferroni, Justin Bayer, Patrick van der Smagt |
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Poster
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Thu 12:00 |
Low Bias Low Variance Gradient Estimates for Hierarchical Boolean Stochastic Networks Adeel Pervez, Taco Cohen, Stratis Gavves |
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Poster
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Thu 13:00 |
A Generative Model for Molecular Distance Geometry Gregor Simm, Jose Miguel Hernandez-Lobato |
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Poster
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Thu 13:00 |
Stochastic Latent Residual Video Prediction Jean-Yves Franceschi, Edouard Delasalles, Mickael Chen, Sylvain Lamprier, Patrick Gallinari |
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Poster
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Thu 13:00 |
Amortised Learning by Wake-Sleep Kevin Wenliang, Theodore Moskovitz, Heishiro Kanagawa, Maneesh Sahani |
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Poster
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Thu 13:00 |
Latent Bernoulli Autoencoder Jiri Fajtl, Vasileios Argyriou, Dorothy Monekosso, Paolo Remagnino |
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Poster
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Thu 14:00 |
Variational Autoencoders with Riemannian Brownian Motion Priors Dimitris Kalatzis, David Eklund, Georgios Arvanitidis, Søren Hauberg |
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Poster
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Thu 14:00 |
The continuous categorical: a novel simplex-valued exponential family Elliott Gordon-Rodriguez, Gabriel Loaiza-Ganem, John Cunningham |
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Poster
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Thu 15:00 |
Reliable Fidelity and Diversity Metrics for Generative Models Ferjad Naeem, Seong Joon Oh, Yunjey Choi, Youngjung Uh, Jaejun Yoo |
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Poster
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Thu 17:00 |
On the Power of Compressed Sensing with Generative Models Akshay Kamath, Eric Price, Sushrut Karmalkar |
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Poster
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Thu 17:00 |
A Graph to Graphs Framework for Retrosynthesis Prediction Chence Shi, Minkai Xu, Hongyu Guo, Ming Zhang, Jian Tang |
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Poster
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Thu 17:00 |
Learning Autoencoders with Relational Regularization Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin |
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Poster
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Thu 17:00 |
Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors Zhaoqiang Liu, Selwyn Gomes, Avtansh Tiwari, Jonathan Scarlett |
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Workshop
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Fri 0:30 |
Invited Talk 2: Bolei Zhou - Interpreting and Leveraging the Latent Semantics in Deep Generative Models Wojciech Samek |
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Workshop
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Fri 2:00 |
Poster session 1 |
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Workshop
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Fri 7:50 |
Learning Affordances in Object-Centric Generative Models Yizhe Wu |
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Workshop
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Fri 8:25 |
Generative Adversarial Set Transformers Karl Stelzner |
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Workshop
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Fri 8:55 |
Poster session and lunch break 1 Workshop CompBio |
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Workshop
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Fri 9:00 |
Poster Session (click to see links) |
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Workshop
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Fri 10:00 |
Poster session and lunch break 2 Workshop CompBio |
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Workshop
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Fri 12:00 |
Spotlight Set 3-3 : Nic Fishman Workshop CompBio |
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Workshop
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Sat 2:25 |
INNF+: Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models Chin-Wei Huang, David Krueger, Rianne Van den Berg, George Papamakarios, Chris Cremer, Ricky T. Q. Chen, Danilo J. Rezende |
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Workshop
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Sat 4:10 |
Invited talk 2: Detecting Distribution Shift with Deep Generative Models Eric Nalisnick |
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Workshop
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Sat 6:00 |
Economics of privacy and data labor Nikolaos Vasiloglou, Rachel Cummings, Glen Weyl, Paris Koutris, Meg Young, Ruoxi Jia, David Dao, Bo Waggoner |
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Workshop
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Sat 7:15 |
"Latent Space Optimization with Deep Generative Models" Jose Miguel Hernandez-Lobato |
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Workshop
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Sat 7:30 |
Invited talk 5: Adversarial Learning of Prescribed Generative Models Adji Bousso Dieng |
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Workshop
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(#67 / Sess. 2) Continuous Graph Flow Zhiwei Deng |