Sequential Event Prediction with Association Rules. - Cynthia Rudin; Benjamin Letham; Ansaf Salleb-Aouissi; Eugene Kogan; David Madigan (COLT, 2011)

An Interpretable Stroke Prediction Model using Rules and Bayesian Analysis. - Benjamin Letham; Cynthia Rudin; Tyler H. McCormick; David Madigan (AAAI (Late-Breaking Developments), 2013)

Growing a list. - Benjamin Letham; Cynthia Rudin; Katherine A. Heller (Data Min. Knowl. Discov., 2013)

Learning theory analysis for association rules and sequential event prediction. - Cynthia Rudin; Benjamin Letham; David Madigan (J. Mach. Learn. Res., 2013)

Sequential event prediction. - Benjamin Letham; Cynthia Rudin; David Madigan (Mach. Learn., 2013)

Latent Variable Copula Inference for Bundle Pricing from Retail Transaction Data. - Benjamin Letham; Wei Sun 031; Anshul Sheopuri (ICML, 2014)

Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model. - Benjamin Letham; Cynthia Rudin; Tyler H. McCormick; David Madigan (CoRR, 2015)

Bayesian Inference of Arrival Rate and Substitution Behavior from Sales Transaction Data with Stockouts. - Benjamin Letham; Lydia M. Letham; Cynthia Rudin (KDD, 2016)

Constrained Bayesian Optimization with Noisy Experiments. - Benjamin Letham; Brian Karrer; Guilherme Ottoni; Eytan Bakshy (CoRR, 2017)

Forecasting at Scale. - Sean J. Taylor; Benjamin Letham (PeerJ Prepr., 2017)

Scalable Meta-Learning for Bayesian Optimization. - Matthias Feurer; Benjamin Letham; Eytan Bakshy (CoRR, 2018)

BoTorch: Programmable Bayesian Optimization in PyTorch. - Maximilian Balandat; Brian Karrer; Daniel R. Jiang; Samuel Daulton; Benjamin Letham; Andrew Gordon Wilson; Eytan Bakshy (CoRR, 2019)

Bayesian Optimization for Policy Search via Online-Offline Experimentation. - Benjamin Letham; Eytan Bakshy (J. Mach. Learn. Res., 2019)

BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization. - Maximilian Balandat; Brian Karrer; Daniel R. Jiang; Samuel Daulton; Benjamin Letham; Andrew Gordon Wilson; Eytan Bakshy (NeurIPS, 2020)

High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization. - Qing Feng; Benjamin Letham; Hongzi Mao; Eytan Bakshy (NeurIPS, 2020)

Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization. - Benjamin Letham; Roberto Calandra; Akshara Rai; Eytan Bakshy (NeurIPS, 2020)

Look-Ahead Acquisition Functions for Bernoulli Level Set Estimation. - Benjamin Letham; Phillip Guan; Chase Tymms; Eytan Bakshy; Michael Shvartsman (AISTATS, 2022)

A Semi-parametric Model for Decision Making in High-Dimensional Sensory Discrimination Tasks. - Stephen Keeley; Benjamin Letham; Craig Sanders; Chase Tymms; Michael Shvartsman (AAAI, 2023)

Sparse Bayesian optimization. - Sulin Liu; Qing Feng; David Eriksson; Benjamin Letham; Eytan Bakshy (AISTATS, 2023)

Perceptual Requirements for World-Locked Rendering in AR and VR. - Phillip Guan; Eric Penner; Joel Hegland; Benjamin Letham; Douglas Lanman (SIGGRAPH Asia, 2023)

Practical Policy Optimization with Personalized Experimentation. - Mia Garrard; Hanson Wang; Ben Letham; Shaun Singh; Abbas Kazerouni; Sarah Tan; Zehui Wang; Yin Huang; Yichun Hu; Chad Zhou; Norm Zhou; Eytan Bakshy (CoRR, 2023)

Response Time Improves Choice Prediction and Function Estimation for Gaussian Process Models of Perception and Preferences. - Michael Shvartsman; Benjamin Letham; Stephen Keeley (CoRR, 2023)

Robust Gaussian Processes via Relevance Pursuit. - Sebastian Ament; Elizabeth Santorella; David Eriksson; Ben Letham; Maximilian Balandat; Eytan Bakshy (NeurIPS, 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)

Response Time Improves Gaussian Process Models for Perception and Preferences. - Michael Shvartsman; Benjamin Letham; Eytan Bakshy; Stephen Keeley (UAI, 2024)

Experimenting, Fast and Slow: Bayesian Optimization of Long-term Outcomes with Online Experiments. - Qing Feng; Samuel Daulton; Benjamin Letham; Maximilian Balandat; Eytan Bakshy (KDD (1), 2025)

Mixed Likelihood Variational Gaussian Processes. - Kaiwen Wu; Craig Sanders; Benjamin Letham; Phillip Guan (CoRR, 2025)