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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 Faster Graph Embeddings via Coarsening
Matthew Fahrbach · Gramoz Goranci · Richard Peng · Sushant Sachdeva · Chi Wang
Poster
Tue 8:00 Meta-learning for Mixed Linear Regression
Weihao Kong · Raghav Somani · Zhao Song · Sham Kakade · Sewoong Oh
Poster
Tue 9:00 How Good is the Bayes Posterior in Deep Neural Networks Really?
Florian Wenzel · Kevin Roth · Bastiaan Veeling · Jakub Swiatkowski · Linh Tran · Stephan Mandt · Jasper Snoek · Tim Salimans · Rodolphe Jenatton · Sebastian Nowozin
Poster
Tue 10:00 Error Estimation for Sketched SVD via the Bootstrap
Miles Lopes · N. Benjamin Erichson · Michael Mahoney
Poster
Tue 10:00 Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free' Dynamical Systems
Hans Kersting · Nicholas Krämer · Martin Schiegg · Christian Daniel · Michael Schober · Philipp Hennig
Poster
Tue 12:00 On Contrastive Learning for Likelihood-free Inference
Conor Durkan · Iain Murray · George Papamakarios
Poster
Tue 13:00 Likelihood-free MCMC with Amortized Approximate Ratio Estimators
Joeri Hermans · Volodimir Begy · Gilles Louppe
Poster
Tue 18:00 Accelerating the diffusion-based ensemble sampling by non-reversible dynamics
Futoshi Futami · Issei Sato · Masashi Sugiyama
Poster
Wed 8:00 Undirected Graphical Models as Approximate Posteriors
Arash Vahdat · Evgeny Andriyash · William Macready
Poster
Wed 8:00 Stochastic Gradient and Langevin Processes
Xiang Cheng · Dong Yin · Peter Bartlett · Michael Jordan
Poster
Wed 8:00 Spectral Graph Matching and Regularized Quadratic Relaxations: Algorithm and Theory
Zhou Fan · Cheng Mao · Yihong Wu · Jiaming Xu