Using Generic Preferences to Incrementally Improve Plan Quality. - Gregg R. Rabideau; Barbara Engelhardt; Steve A. Chien (AIPS, 2000)

Empirical Evaluation of Local Search Methods for Adapting Planning Policies in a Stochastic Environment. - Barbara Engelhardt; Steve A. Chien (Local Search for Planning and Scheduling, 2000)

A Tool for Autonomous Ground-Based Rover Planning. - Rob Sherwood; Andrew Mishkin; Tara A. Estlin; Steve A. Chien; Barbara Engelhardt; Brian K. Cooper; Gregg R. Rabideau (FLAIRS, 2001)

Balancing deliberation and reaction, planning and execution for space robotic applications. - Russell Knight; Forest Fisher; Tara A. Estlin; Barbara Engelhardt; Steve A. Chien (IROS, 2001)

Casper: Space Exploration through Continuous Planning. - Russell Knight; Gregg R. Rabideau; Steve A. Chien; Barbara Engelhardt; Rob Sherwood (IEEE Intell. Syst., 2001)

The RADARSAT-MAMM Automated Mission Planner. - Benjamin D. Smith; Barbara E. Engelhardt; Darren H. Mutz (AI Mag., 2002)

Factored Planning. - Eyal Amir; Barbara Engelhardt (IJCAI, 2003)

Protein Molecular Function Prediction by Bayesian Phylogenomics. - Barbara E. Engelhardt; Michael I. Jordan; Kathryn E. Muratore; Steven E. Brenner (PLoS Comput. Biol., 2005)

A graphical model for predicting protein molecular function. - Barbara E. Engelhardt; Michael I. Jordan; Steven E. Brenner (ICML, 2006)

Stability selection for regression-based models of transcription factor-DNA binding specificity. - Fantine Mordelet; John Horton; Alexander J. Hartemink; Barbara E. Engelhardt; Raluca Gordân (Bioinform., 2013)

Clustering with Beta Divergences. - Mehmet Emin Basbug; Barbara E. Engelhardt (CoRR, 2015)

Hierarchical Compound Poisson Factorization. - Mehmet Emin Basbug; Barbara E. Engelhardt (ICML, 2016)

Fast moment estimation for generalized latent Dirichlet models. - Shiwen Zhao; Barbara E. Engelhardt; Sayan Mukherjee 001; David B. Dunson (CoRR, 2016)

Bayesian group factor analysis with structured sparsity. - Shiwen Zhao; Chuan Gao; Sayan Mukherjee 001; Barbara E. Engelhardt (J. Mach. Learn. Res., 2016)

Context Specific and Differential Gene Co-expression Networks via Bayesian Biclustering. - Chuan Gao; Ian C. McDowell; Shiwen Zhao; Christopher D. Brown; Barbara E. Engelhardt (PLoS Comput. Biol., 2016)

Dynamic Collaborative Filtering With Compound Poisson Factorization. - Ghassen Jerfel; Mehmet Emin Basbug; Barbara E. Engelhardt (AISTATS, 2017)

A Reinforcement Learning Approach to Weaning of Mechanical Ventilation in Intensive Care Units. - Niranjani Prasad; Li-Fang Cheng; Corey Chivers; Michael Draugelis; Barbara E. Engelhardt (UAI, 2017)

Coupled Compound Poisson Factorization. - Mehmet Emin Basbug; Barbara E. Engelhardt (CoRR, 2017)

Adaptive Randomized Dimension Reduction on Massive Data. - Gregory Darnell; Stoyan Georgiev; Sayan Mukherjee 001; Barbara E. Engelhardt (J. Mach. Learn. Res., 2017)

The impact of rare variation on gene expression across tissues. - Xin Li 130; Yungil Kim; Emily K. Tsang; Joe R. Davis; Farhan N. Damani; Colby Chiang; Gaelen T. Hess; Zachary Zappala; Benjamin J. Strober; Alexandra J. Scott; Amy Li; Andrea Ganna; et al. (Nat., 2017)

PG-TS: Improved Thompson Sampling for Logistic Contextual Bandits. - Bianca Dumitrascu; Karen Feng; Barbara E. Engelhardt (NeurIPS, 2018)

How algorithmic confounding in recommendation systems increases homogeneity and decreases utility. - Allison June-Barlow Chaney; Brandon M. Stewart; Barbara E. Engelhardt (RecSys, 2018)

Clustering gene expression time series data using an infinite Gaussian process mixture model. - Ian C. McDowell; Dinesh Manandhar; Christopher M. Vockley; Amy K. Schmid; Timothy E. Reddy; Barbara E. Engelhardt (PLoS Comput. Biol., 2018)

Predicting Sick Patient Volume in a Pediatric Outpatient Setting using Time Series Analysis. - Grace Guan; Barbara E. Engelhardt (MLHC, 2019)

An Optimal Policy for Patient Laboratory Tests in Intensive Care Units. - Li-Fang Cheng; Niranjani Prasad; Barbara E. Engelhardt (PSB, 2019)

netNMF-sc: A Network Regularization Algorithm for Dimensionality Reduction and Imputation of Single-Cell Expression Data. - Rebecca Elyanow; Bianca Dumitrascu; Barbara E. Engelhardt; Benjamin J. Raphael (RECOMB, 2019)

End-to-end Training of Deep Probabilistic CCA on Paired Biomedical Observations. - Gregory W. Gundersen; Bianca Dumitrascu; Jordan T. Ash; Barbara E. Engelhardt (UAI, 2019)

Statistical tests for detecting variance effects in quantitative trait studies. - Bianca Dumitrascu; Gregory Darnell; Julien Ayroles; Barbara E. Engelhardt (Bioinform., 2019)

Defining Admissible Rewards for High Confidence Policy Evaluation. - Niranjani Prasad; Barbara E. Engelhardt; Finale Doshi-Velez (CoRR, 2019)

Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes. - Li-Fang Cheng; Bianca Dumitrascu; Michael Minyi Zhang; Corey Chivers; Michael Draugelis; Kai Li 001; Barbara E. Engelhardt (AISTATS, 2020)

Defining admissible rewards for high-confidence policy evaluation in batch reinforcement learning. - Niranjani Prasad; Barbara E. Engelhardt; Finale Doshi-Velez (CHIL, 2020)

A robust nonlinear low-dimensional manifold for single cell RNA-seq data. - Archit Verma; Barbara E. Engelhardt (BMC Bioinform., 2020)

Nonparametric Deconvolution Models. - Allison June-Barlow Chaney; Archit Verma; Young-Suk Lee; Barbara E. Engelhardt (CoRR, 2020)

Probabilistic Contrastive Principal Component Analysis. - Didong Li; Andrew Jones; Barbara E. Engelhardt (CoRR, 2020)

Sparse multi-output Gaussian processes for online medical time series prediction. - Li-Fang Cheng; Bianca Dumitrascu; Gregory Darnell; Corey Chivers; Michael Draugelis; Kai Li 001; Barbara E. Engelhardt (BMC Medical Informatics Decis. Mak., 2020)

Latent variable modeling with random features. - Gregory W. Gundersen; Michael Minyi Zhang; Barbara E. Engelhardt (AISTATS, 2021)

COP-E-CAT: cleaning and organization pipeline for EHR computational and analytic tasks. - Aishwarya Mandyam; Elizabeth C. Yoo; Jeff Soules; Krzysztof Laudanski; Barbara E. Engelhardt (BCB, 2021)

Active multi-fidelity Bayesian online changepoint detection. - Gregory W. Gundersen; Diana Cai; Chuteng Zhou; Barbara E. Engelhardt; Ryan P. Adams (UAI, 2021)

Nested Policy Reinforcement Learning. - Aishwarya Mandyam; Andrew Jones; Krzysztof Laudanski; Barbara E. Engelhardt (CoRR, 2021)

Nonnegative spatial factorization. - F. William Townes; Barbara E. Engelhardt (CoRR, 2021)

Brain kernel: A new spatial covariance function for fMRI data. - Anqi Wu; Samuel A. Nastase; Christopher Baldassano; Nicholas B. Turk-Browne; Kenneth A. Norman; Barbara E. Engelhardt; Jonathan W. Pillow (NeuroImage, 2021)

Causal network inference from gene transcriptional time-series response to glucocorticoids. - Jonathan Lu; Bianca Dumitrascu; Ian C. McDowell; Brian Jo; Alejandro Barrera; Linda K. Hong; Sarah M. Leichter; Timothy E. Reddy; Barbara E. Engelhardt (PLoS Comput. Biol., 2021)

Variance Minimization in the Wasserstein Space for Invariant Causal Prediction. - Guillaume G. Martinet; Alexander Strzalkowski; Barbara E. Engelhardt (AISTATS, 2022)

A Poisson reduced-rank regression model for association mapping in sequencing data. - Tiana Fitzgerald; Andrew Jones; Barbara E. Engelhardt (BMC Bioinform., 2022)

Compositional Q-learning for electrolyte repletion with imbalanced patient sub-populations. - Aishwarya Mandyam; Andrew Jones; Jiayu Yao; Krzysztof Laudanski; Barbara E. Engelhardt (ML4H@NeurIPS, 2023)

Kernel Density Bayesian Inverse Reinforcement Learning. - Aishwarya Mandyam; Didong Li; Diana Cai; Andrew Jones; Barbara E. Engelhardt (CoRR, 2023)

Bayesian Non-linear Latent Variable Modeling via Random Fourier Features. - Michael Minyi Zhang; Gregory W. Gundersen; Barbara E. Engelhardt (CoRR, 2023)

Adaptive Interventions with User-Defined Goals for Health Behavior Change. - Aishwarya Mandyam; Matthew Jörke; Barbara E. Engelhardt; Emma Brunskill (CoRR, 2023)

Sequential Gaussian Processes for Online Learning of Nonstationary Functions. - Michael Minyi Zhang; Bianca Dumitrascu; Sinead A. Williamson; Barbara E. Engelhardt (IEEE Trans. Signal Process., 2023)

Automating Transparency Mechanisms in the Judicial System Using LLMs: Opportunities and Challenges. - Ishana Shastri; Shomik Jain; Barbara Engelhardt; Ashia Wilson (AIES (1), 2024)

Adaptive Interventions with User-Defined Goals for Health Behavior Change. - Aishwarya Mandyam; Matthew Jörke; William Denton; Barbara E. Engelhardt; Emma Brunskill (CHIL, 2024)

Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes. - Syrine Belakaria; Ben Letham; Jana Doppa; Barbara Engelhardt; Stefano Ermon; Eytan Bakshy (NeurIPS, 2024)

Inverse Reinforcement Learning with Multiple Planning Horizons. - Jiayu Yao; Weiwei Pan; Finale Doshi-Velez; Barbara E. Engelhardt (RLJ, 2024)

CANDOR: Counterfactual ANnotated DOubly Robust Off-Policy Evaluation. - Aishwarya Mandyam; Shengpu Tang; Jiayu Yao; Jenna Wiens; Barbara E. Engelhardt (CoRR, 2024)

KD-BIRL: Kernel Density Bayesian Inverse Reinforcement Learning. - Aishwarya Mandyam; Didong Li; Andrew Jones; Diana Cai; Barbara E. Engelhardt (Trans. Mach. Learn. Res., 2024)

Answering open questions in biology using spatial genomics and structured methods. - Siddhartha G. Jena; Archit Verma; Barbara E. Engelhardt (BMC Bioinform., 2024)

Non-Myopic Multi-Objective Bayesian Optimization. - Syrine Belakaria; Alaleh Ahmadianshalchi; Barbara E. Engelhardt; Stefano Ermon; Jana Doppa (Trans. Mach. Learn. Res., 2025)

A Distributional Evaluation of Generative Image Models. - Edric Tam; Barbara E. Engelhardt (CoRR, 2025)

Preference-Guided Diffusion for Multi-Objective Offline Optimization. - Yashas Annadani; Syrine Belakaria; Stefano Ermon; Stefan Bauer; Barbara E. Engelhardt (CoRR, 2025)

Sharpe Ratio-Guided Active Learning for Preference Optimization in RLHF. - Syrine Belakaria; Joshua Kazdan; Charles Marx; Chris Cundy; Willie Neiswanger; Sanmi Koyejo; Barbara E. Engelhardt; Stefano Ermon (CoRR, 2025)

PERRY: Policy Evaluation with Confidence Intervals using Auxiliary Data. - Aishwarya Mandyam; Jason Meng; Ge Gao; Jiankai Sun; Mac Schwager; Barbara E. Engelhardt; Emma Brunskill (CoRR, 2025)