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22 Results

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Poster
Mon 2:30 Denoising Diffusion Samplers
Francisco Vargas · Will Grathwohl · Arnaud Doucet
Poster
Approximate Bayesian Inference with Stein Functional Variational Gradient Descent
Tobias Pielok · Bernd Bischl · David Rügamer
Poster
Wed 2:30 Calibrating Transformers via Sparse Gaussian Processes
Wenlong Chen · Yingzhen Li
Poster
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach
Han Guo · Philip Greengard · Hongyi Wang · Andrew Gelman · Yoon Kim · Eric Xing
Poster
Learnable Topological Features For Phylogenetic Inference via Graph Neural Networks
Cheng Zhang
Poster
Semi-Implicit Variational Inference via Score Matching
Longlin Yu · Cheng Zhang
Poster
Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions
Raghav Singhal · Mark Goldstein · Rajesh Ranganath
Poster
Tue 7:30 Energy-Based Test Sample Adaptation for Domain Generalization
Zehao Xiao · Xiantong Zhen · Shengcai Liao · Cees G Snoek
Poster
Deep Variational Implicit Processes
Luis A. Ortega · Simon Rodriguez · Daniel Hernández-Lobato
Poster
Wed 2:30 Particle-based Variational Inference with Preconditioned Functional Gradient Flow
Hanze Dong · Xi Wang · LIN Yong · Tong Zhang
Poster
Mon 7:30 Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning
Matthew Ashman · Chao Ma · Agrin Hilmkil · Joel Jennings · Cheng Zhang
Poster
Benchmarking Constraint Inference in Inverse Reinforcement Learning
Guiliang Liu · Yudong Luo · Ashish Gaurav · Kasra Rezaee · Pascal Poupart