Gene function classification using Bayesian models with hierarchy-based priors. - Babak Shahbaba; Radford M. Neal (BMC Bioinform., 2006)

A modified Dirichlet process mixture model for clustering phosphopeptides based on their response to anti-cancer drug perturbation. - Babak Shahbaba; Eva Prenosil; Anjali Jain; Sylvia K. Plevritis (BIOCOMP, 2008)

Nonlinear Models Using Dirichlet Process Mixtures. - Babak Shahbaba; Radford M. Neal (J. Mach. Learn. Res., 2009)

Wormhole Hamiltonian Monte Carlo. - Shiwei Lan; Jeffrey Streets; Babak Shahbaba (AAAI, 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 003; Babak Shahbaba (ICML, 2014)

A Semiparametric Bayesian Model for Detecting Synchrony Among Multiple Neurons. - Babak Shahbaba; Bo Zhou 003; Shiwei Lan; Hernando Ombao; David Moorman; Sam Behseta (Neural Comput., 2014)

Split Hamiltonian Monte Carlo. - Babak Shahbaba; Shiwei Lan; Wesley O. Johnson; Radford M. Neal (Stat. Comput., 2014)

An efficient Bayesian inference framework for coalescent-based nonparametric phylodynamics. - Shiwei Lan; Julia A. Palacios; Michael D. Karcher; Vladimir N. Minin; Babak Shahbaba (Bioinform., 2015)

What time is it? Deep learning approaches for circadian rhythms. - Forest Agostinelli; Nicholas Ceglia; Babak Shahbaba; Paolo Sassone-Corsi; Pierre Baldi (Bioinform., 2016)

Precomputing strategy for Hamiltonian Monte Carlo method based on regularity in parameter space. - Cheng Zhang; Babak Shahbaba; Hongkai Zhao (Comput. Stat., 2017)

Hamiltonian Monte Carlo acceleration using surrogate functions with random bases. - Cheng Zhang; Babak Shahbaba; Hongkai Zhao (Stat. Comput., 2017)

Modeling Binary Time Series Using Gaussian Processes with Application to Predicting Sleep States. - Xu Gao; Babak Shahbaba; Hernando C. Ombao (J. Classif., 2018)

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

Bayesian Neural Decoding Using A Diversity-Encouraging Latent Representation Learning Method. - Tian Chen; Lingge Li; Gabriel Elias; Norbert Fortin; Babak Shahbaba (CoRR, 2019)

Neural network gradient Hamiltonian Monte Carlo. - Lingge Li; Andrew Holbrook; Babak Shahbaba; Pierre Baldi (Comput. Stat., 2019)

Nonparametric Fisher Geometry with Application to Density Estimation. - Andrew Holbrook; Shiwei Lan; Jeffrey Streets; Babak Shahbaba (UAI, 2020)

Conjoined Dirichlet Process. - Michelle N. Ngo; Dustin S. Pluta; Alexander N. Ngo; Babak Shahbaba (CoRR, 2020)

Brain waves analysis via a non-parametric Bayesian mixture of autoregressive kernels. - Guilllermo Granados-Garcia; Mark Fiecas; Babak Shahbaba; Norbert Fortin; Hernando C. Ombao (Comput. Stat. Data Anal., 2022)

Hippocampal ensembles represent sequential relationships among an extended sequence of nonspatial events. - Babak Shahbaba; Lingge Li; Forest Agostinelli; Mansi Saraf; Keiland W. Cooper; Derenik Haghverdian; Gabriel A. Elias; Pierre Baldi; Norbert J. Fortin (Zenodo, 2022)

Scaling Up Bayesian Uncertainty Quantification for Inverse Problems Using Deep Neural Networks. - Shiwei Lan; Shuyi Li; Babak Shahbaba (SIAM/ASA J. Uncertain. Quantification, 2022)

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

A Model-Agnostic Graph Neural Network for Integrating Local and Global Information. - Wenzhuo Zhou; Annie Qu; Keiland W. Cooper; Norbert Fortin; Babak Shahbaba (CoRR, 2023)

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 (NeurIPS, 2024)

Optimal Transport for Latent Integration with An Application to Heterogeneous Neuronal Activity Data. - Yubai Yuan; Babak Shahbaba; Norbert Fortin; Keiland W. Cooper; Qing Nie; Annie Qu (CoRR, 2024)

Weakly-Supervised Multimodal Learning on MIMIC-CXR. - Andrea Agostini; Daphné Chopard; Yang Meng; Norbert Fortin; Babak Shahbaba; Stephan Mandt; Thomas M. Sutter; Julia E. Vogt (CoRR, 2024)

Scaling Up Bayesian Neural Networks with Neural Networks. - Zahra Moslemi; Yang Meng; Shiwei Lan; Babak Shahbaba (Trans. Mach. Learn. Res., 2024)

Reinforcement Learning for Individual Optimal Policy from Heterogeneous Data. - Rui Miao; Babak Shahbaba; Annie Qu (CoRR, 2025)

Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning. - Ziyi Liang; Annie Qu; Babak Shahbaba (CoRR, 2025)