Shahbaba, Babak

9 publications

TMLR 2024 Scaling up Bayesian Neural Networks with Neural Networks Zahra Moslemi, Yang Meng, Shiwei Lan, Babak Shahbaba

NeurIPS 2024 Unity by Diversity: Improved Representation Learning for Multimodal VAEs Thomas M. Sutter, Yang Meng, Andrea Agostini, Daphné Chopard, Norbert Fortin, Julia E. Vogt, Babak Shahbaba, Stephan Mandt

ICML 2023 Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes Ba-Hien Tran, Babak Shahbaba, Stephan Mandt, Maurizio Filippone

UAI 2020 Nonparametric Fisher Geometry with Application to Density Estimation Andrew Holbrook, Shiwei Lan, Jeffrey Streets, Babak Shahbaba

NeurIPS 2019 Modeling Dynamic Functional Connectivity with Latent Factor Gaussian Processes Lingge Li, Dustin Pluta, Babak Shahbaba, Norbert Fortin, Hernando Ombao, Pierre Baldi

ICML 2014 Distributed Stochastic Gradient MCMC Sungjin Ahn, Babak Shahbaba, Max Welling

ICML 2014 Spherical Hamiltonian Monte Carlo for Constrained Target Distributions Shiwei Lan, Bo Zhou, Babak Shahbaba

AAAI 2014 Wormhole Hamiltonian Monte Carlo Shiwei Lan, Jeffrey Streets, Babak Shahbaba

JMLR 2009 Nonlinear Models Using Dirichlet Process Mixtures Babak Shahbaba, Radford Neal