Poster

Thu 7:00

Provable Smoothness Guarantees for Black-Box Variational Inference
Justin Domke

Poster

Thu 7:00

Variational Inference for Sequential Data with Future Likelihood Estimates
Geon-Hyeong Kim · Youngsoo Jang · Hongseok Yang · Kee-Eung Kim

Poster

Thu 17:00

On the (In)tractability of Computing Normalizing Constants for the Product of Determinantal Point Processes
Naoto Ohsaka · Tatsuya Matsuoka

Poster

Thu 7:00

Variance Reduction and Quasi-Newton for Particle-Based Variational Inference
Michael Zhu · Chang Liu · Jun Zhu

Poster

Wed 10:00

Batch Stationary Distribution Estimation
Junfeng Wen · Bo Dai · Lihong Li · Dale Schuurmans

Poster

Thu 6:00

Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics
Matthew Hoffman · Yian Ma

Poster

Tue 13:00

Likelihood-free MCMC with Amortized Approximate Ratio Estimators
Joeri Hermans · Volodimir Begy · Gilles Louppe

Poster

Wed 8:00

Stochastic Gradient and Langevin Processes
Xiang Cheng · Dong Yin · Peter Bartlett · Michael Jordan

Poster

Tue 10:00

Error Estimation for Sketched SVD via the Bootstrap
Miles Lopes · N. Benjamin Erichson · Michael Mahoney

Poster

Wed 12:00

Automatic Reparameterisation of Probabilistic Programs
Maria Gorinova · Dave Moore · Matthew Hoffman

Poster

Thu 12:00

Double-Loop Unadjusted Langevin Algorithm
Paul Rolland · Armin Eftekhari · Ali Kavis · Volkan Cevher

Poster

Wed 8:00

Undirected Graphical Models as Approximate Posteriors
Arash Vahdat · Evgeny Andriyash · William Macready