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Oral
Tue Jun 11th 11:00 -- 11:20 AM @ Room 101
A Contrastive Divergence for Combining Variational Inference and MCMC
Francisco Ruiz · Michalis Titsias
Oral
Tue Jun 11th 11:20 -- 11:25 AM @ Room 101
Calibrated Approximate Bayesian Inference
Hanwen Xing · Geoff Nicholls · Jeong Lee
Oral
Tue Jun 11th 11:25 -- 11:30 AM @ Room 101
Moment-Based Variational Inference for Markov Jump Processes
Christian Wildner · Heinz Koeppl
Oral
Tue Jun 11th 11:30 -- 11:35 AM @ Room 101
Understanding MCMC Dynamics as Flows on the Wasserstein Space
Chang Liu · Jingwei Zhuo · Jun Zhu
Oral
Tue Jun 11th 11:35 -- 11:40 AM @ Room 101
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations
Brian Trippe · Jonathan Huggins · Raj Agrawal · Tamara Broderick
Oral
Tue Jun 11th 11:40 AM -- 12:00 PM @ Room 101
Amortized Monte Carlo Integration
Adam Golinski · Frank Wood · Tom Rainforth
Oral
Tue Jun 11th 12:00 -- 12:05 PM @ Room 101
Stein Point Markov Chain Monte Carlo
Wilson Ye Chen · Alessandro Barp · Francois-Xavier Briol · Jackson Gorham · Mark Girolami · Lester Mackey · Chris Oates
Oral
Tue Jun 11th 12:05 -- 12:10 PM @ Room 101
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations
Wu Lin · Mohammad Emtiyaz Khan · Mark Schmidt
Oral
Tue Jun 11th 12:10 -- 12:15 PM @ Room 101
Particle Flow Bayes' Rule
Xinshi Chen · Hanjun Dai · Le Song
Oral
Tue Jun 11th 12:15 -- 12:20 PM @ Room 101
Correlated Variational Auto-Encoders
Da Tang · Dawen Liang · Tony Jebara · Nicholas Ruozzi