110 Results

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 On Implicit Regularization in $\beta$-VAEs
Abhishek Kumar, Ben Poole
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 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 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 Learning from Irregularly-Sampled Time Series: A Missing Data Perspective
Steve Li, Benjamin M Marlin
Poster
Tue 7:00 Recurrent Hierarchical Topic-Guided RNN for Language Generation
Dandan Guo, Bo Chen, Ruiying Lu, Mingyuan Zhou
Poster
Tue 8:00 Near-optimal sample complexity bounds for learning Latent $k-$polytopes and applications to Ad-Mixtures
Chiru Bhattacharyya, Ravindran Kannan
Poster
Tue 8:00 Associative Memory in Iterated Overparameterized Sigmoid Autoencoders
Yibo Jiang, Cengiz Pehlevan
Poster
Tue 9:00 Feature Quantization Improves GAN Training
Yang Zhao, Chunyuan Li, Iris Yu, Jianfeng Gao, Changyou Chen
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 Scalable Deep Generative Modeling for Sparse Graphs
Hanjun Dai, Azade Nazi, Yujia Li, Bo Dai, Dale Schuurmans
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 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 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 Incremental Sampling Without Replacement for Sequence Models
Kensen Shi, David Bieber, Charles Sutton
Poster
Tue 12:00 On Contrastive Learning for Likelihood-free Inference
Conor Durkan, Iain Murray, George Papamakarios
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 13:00 Predictive Sampling with Forecasting Autoregressive Models
Auke Wiggers, Emiel Hoogeboom
Poster
Tue 13:00 Latent Space Factorisation and Manipulation via Matrix Subspace Projection
Xiao Li, Chenghua Lin, Ruizhe Li, Chaozheng Wang, Frank Guerin
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 15:00 Invertible generative models for inverse problems: mitigating representation error and dataset bias
Muhammad Asim, Max Daniels, Oscar Leong, Ali Ahmed, Paul Hand
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 VFlow: More Expressive Generative Flows with Variational Data Augmentation
Jianfei Chen, Cheng Lu, Biqi Chenli, Jun Zhu, Tian Tian
Poster
Wed 5:00 Learning Structured Latent Factors from Dependent Data:A Generative Model Framework from Information-Theoretic Perspective
Ruixiang ZHANG, Masanori Koyama, Katsuhiko Ishiguro
Poster
Wed 5:00 Hierarchical Generation of Molecular Graphs using Structural Motifs
Wengong Jin, Regina Barzilay, Tommi Jaakkola
Poster
Wed 5:00 Convolutional dictionary learning based auto-encoders for natural exponential-family distributions
Bahareh Tolooshams, Andrew Song, Simona Temereanca, Demba Ba
Poster
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
Poster
Wed 8:00 Undirected Graphical Models as Approximate Posteriors
Arash Vahdat, Evgeny Andriyash, William Macready
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 The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
Bin Dai, Ziyu Wang, David Wipf
Poster
Wed 8:00 Sample Amplification: Increasing Dataset Size even when Learning is Impossible
Brian Axelrod, Shivam Garg, Vatsal Sharan, Gregory Valiant
Poster
Wed 8:00 Optimal transport mapping via input convex neural networks
Ashok Makkuva, Amir Taghvaei, Sewoong Oh, Jason Lee
Poster
Wed 10:00 Learning Calibratable Policies using Programmatic Style-Consistency
Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew Hausknecht
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 11:00 PolyGen: An Autoregressive Generative Model of 3D Meshes
Charlie Nash, Yaroslav Ganin, S. M. Ali Eslami, Peter Battaglia
Poster
Wed 11:00 Deep Gaussian Markov Random Fields
Per Sidén, Fredrik Lindsten
Poster
Wed 11:00 Multilinear Latent Conditioning for Generating Unseen Attribute Combinations
Markos Georgopoulos, Grigorios Chrysos, Maja Pantic, Yannis Panagakis
Poster
Wed 12:00 Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows
Rob Cornish, Anthony Caterini, George Deligiannidis, Arnaud Doucet
Poster
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
Poster
Wed 12:00 Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables
Q. Wang, Herke van Hoof
Poster
Wed 13:00 Continuous Time Bayesian Networks with Clocks
Nicolai Engelmann, Dominik Linzner, Heinz Koeppl
Poster
Wed 16:00 On Relativistic f-Divergences
Alexia Jolicoeur-Martineau
Poster
Wed 16:00 Spread Divergence
Mingtian Zhang, Peter Hayes, Thomas Bird, Raza Habib, David Barber
Poster
Thu 6:00 Causal Inference using Gaussian Processes with Structured Latent Confounders
Sam Witty, Kenta Takatsu, David Jensen, Vikash Mansinghka
Poster
Thu 6:00 Bridging the Gap Between f-GANs and Wasserstein GANs
Jiaming Song, Stefano Ermon
Poster
Thu 6:00 How to Train Your Neural ODE: the World of Jacobian and Kinetic Regularization
Chris Finlay, Jörn Jacobsen, Levon Nurbekyan, Adam Oberman
Poster
Thu 6:00 On Breaking Deep Generative Model-based Defenses and Beyond
Yanzhi Chen, Renjie Xie, Zhanxing Zhu
Poster
Thu 6:00 GraphOpt: Learning Optimization Models of Graph Formation
Rakshit Trivedi, Jiachen Yang, Hongyuan Zha
Poster
Thu 6:00 Robustifying Sequential Neural Processes
Jaesik Yoon, Gautam Singh, Sungjin Ahn
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 Tails of Lipschitz Triangular Flows
Priyank Jaini, Ivan Kobyzev, Yaoliang Yu, Marcus Brubaker
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 Learning with Normalizing Flows
Pavel Izmailov, Polina Kirichenko, Marc Finzi, Andrew Wilson
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 StyleGAN for Disentanglement Learning
Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit Patel, Anima Anandkumar
Poster
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
Poster
Thu 7:00 Fractal Gaussian Networks: A sparse random graph model based on Gaussian Multiplicative Chaos
Subhroshekhar Ghosh, Krishna Balasubramanian, Xiaochuan Yang
Poster
Thu 7:00 Variational Inference for Sequential Data with Future Likelihood Estimates
Geon-Hyeong Kim, Baezii RL, Hongseok Yang, Kee-Eung Kim
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 Time-aware Large Kernel Convolutions
Vasileios Lioutas, Yuhong Guo
Poster
Thu 7:00 Perceptual Generative Autoencoders
Zijun Zhang, Ruixiang ZHANG, Zongpeng Li, Yoshua Bengio, Liam Paull
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 8:00 SGD Learns One-Layer Networks in WGANs
Qi Lei, Jason Lee, Alex Dimakis, Constantinos Daskalakis
Poster
Thu 8:00 Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems
Zhe Dong, Bryan Seybold, Kevin Murphy, Hung Bui
Poster
Thu 8:00 AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation
Jae Hyun Lim, Aaron Courville, Christopher Pal, Chin-Wei Huang
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 9:00 Energy-Based Processes for Exchangeable Data
Mengjiao Yang, Bo Dai, Hanjun Dai, Dale Schuurmans
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 A Generative Model for Molecular Distance Geometry
Gregor Simm, Jose Miguel Hernandez-Lobato
Poster
Thu 13:00 Stochastic Latent Residual Video Prediction
Jean-Yves Franceschi, Edouard Delasalles, Mickael Chen, Sylvain Lamprier, Patrick Gallinari
Poster
Thu 13:00 Amortised Learning by Wake-Sleep
Kevin Wenliang, Theodore Moskovitz, Heishiro Kanagawa, Maneesh Sahani
Poster
Thu 13:00 Latent Bernoulli Autoencoder
Jiri Fajtl, Vasileios Argyriou, Dorothy Monekosso, Paolo Remagnino
Poster
Thu 14:00 Variational Autoencoders with Riemannian Brownian Motion Priors
Dimitris Kalatzis, David Eklund, Georgios Arvanitidis, Søren Hauberg
Poster
Thu 14:00 The continuous categorical: a novel simplex-valued exponential family
Elliott Gordon-Rodriguez, Gabriel Loaiza-Ganem, John Cunningham
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
Poster
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
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
Fri 7:50 Learning Affordances in Object-Centric Generative Models
Yizhe Wu
Workshop
Fri 8:25 Generative Adversarial Set Transformers
Karl Stelzner
Workshop
Fri 8:55 Poster session and lunch break 1
Workshop CompBio
Workshop
Fri 9:00 Poster Session (click to see links)
Workshop
Fri 10:00 Poster session and lunch break 2
Workshop CompBio
Workshop
Fri 12:00 Spotlight Set 3-3 : Nic Fishman
Workshop CompBio
Workshop
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
Workshop
Sat 4:10 Invited talk 2: Detecting Distribution Shift with Deep Generative Models
Eric Nalisnick
Workshop
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
Workshop
Sat 7:15 "Latent Space Optimization with Deep Generative Models"
Jose Miguel Hernandez-Lobato
Workshop
Sat 7:30 Invited talk 5: Adversarial Learning of Prescribed Generative Models
Adji Bousso Dieng
Workshop
(#67 / Sess. 2) Continuous Graph Flow
Zhiwei Deng