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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
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
Tue 7:00 ControlVAE: Controllable Variational Autoencoder
Huajie Shao · Shuochao Yao · Dachun Sun · Aston Zhang · Shengzhong Liu · Dongxin Liu · Jun Wang · Tarek Abdelzaher
Tue 7:00 Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling
Will Grathwohl · Kuan-Chieh Wang · Joern-Henrik Jacobsen · David Duvenaud · Richard Zemel
Tue 7:00 Recurrent Hierarchical Topic-Guided RNN for Language Generation
Dandan Guo · Bo Chen · Ruiying Lu · Mingyuan Zhou
Tue 7:00 Learning from Irregularly-Sampled Time Series: A Missing Data Perspective
Steven Cheng-Xian Li · Benjamin M Marlin
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
Tue 7:00 Generative Flows with Matrix Exponential
Changyi Xiao · Ligang Liu
Tue 7:00 On Implicit Regularization in $\beta$-VAEs
Abhishek Kumar · Ben Poole
Tue 7:00 Fair Generative Modeling via Weak Supervision
Kristy Choi · Aditya Grover · Trisha Singh · Rui Shu · Stefano Ermon
Tue 7:00 Evaluating Lossy Compression Rates of Deep Generative Models
Sicong Huang · Alireza Makhzani · Yanshuai Cao · Roger Grosse
Tue 8:00 Near-optimal sample complexity bounds for learning Latent $k-$polytopes and applications to Ad-Mixtures
Chiranjib Bhattacharyya · Ravindran Kannan