Efficient Value Iteration Using Partitioned Models. - David Wingate; Kevin D. Seppi (ICMLA, 2003)

P3VI: a partitioned, prioritized, parallel value iterator. - David Wingate; Kevin D. Seppi (ICML, 2004)

Variable resolution discretization in the joint space. - Christopher K. Monson; David Wingate; Kevin D. Seppi; Todd S. Peterson (ICMLA, 2004)

Prioritized Multiplicative Schwarz Procedures for Solving Linear Systems. - David Wingate; Nathaniel Powell; Quinn Snell; Kevin D. Seppi (IPDPS, 2005)

Predictive Linear-Gaussian Models of Stochastic Dynamical Systems. - Matthew R. Rudary; Satinder Singh 001; David Wingate (UAI, 2005)

Prioritization Methods for Accelerating MDP Solvers. - David Wingate; Kevin D. Seppi (J. Mach. Learn. Res., 2005)

Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems. - David Wingate; Satinder Singh 001 (AAAI, 2006)

Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems. - David Wingate; Satinder Singh 001 (ICML, 2006)

On discovery and learning of models with predictive representations of state for agents with continuous actions and observations. - David Wingate; Satinder Singh 001 (AAMAS, 2007)

Relational Knowledge with Predictive State Representations. - David Wingate; Vishal Soni; Britton Wolfe; Satinder Singh 001 (IJCAI, 2007)

Exponential Family Predictive Representations of State. - David Wingate; Satinder Singh 001 (NIPS, 2007)

Sigma point policy iteration. - Michael H. Bowling; Alborz Geramifard; David Wingate (AAMAS (1), 2008)

Efficiently learning linear-linear exponential family predictive representations of state. - David Wingate; Satinder Singh 001 (ICML, 2008)

Exponential Family Predictive Representations of State. - David Wingate (2008)

Workshop summary: Results of the 2009 reinforcement learning competition. - David Wingate; Carlos Diuk; Lihong Li 001; Matthew Taylor; Jordan Frank (ICML, 2009)

A Bayesian Sampling Approach to Exploration in Reinforcement Learning. - John Asmuth; Lihong Li 001; Michael L. Littman; Ali Nouri; David Wingate (UAI, 2009)

The Infinite Latent Events Model. - David Wingate; Noah D. Goodman; Daniel M. Roy 001; Joshua B. Tenenbaum (UAI, 2009)

Smartlocks: lock acquisition scheduling for self-aware synchronization. - Jonathan Eastep; David Wingate; Marco D. Santambrogio; Anant Agarwal (ICAC, 2010)

Nonparametric Bayesian Policy Priors for Reinforcement Learning. - Finale Doshi-Velez; David Wingate; Nicholas Roy; Joshua B. Tenenbaum (NIPS, 2010)

An expanding reference library for Peer-to-Peer content. - Jason Valdez; Mina Guirguis; David Wingate; Rory Rinkevich (eCrime Researchers Summit, 2011)

Smart data structures: an online machine learning approach to multicore data structures. - Jonathan Eastep; David Wingate; Anant Agarwal (ICAC, 2011)

Infinite Dynamic Bayesian Networks. - Finale Doshi; David Wingate; Joshua B. Tenenbaum; Nicholas Roy (ICML, 2011)

Bayesian Policy Search with Policy Priors. - David Wingate; Noah D. Goodman; Daniel M. Roy 001; Leslie Pack Kaelbling; Joshua B. Tenenbaum (IJCAI, 2011)

Nonstandard Interpretations of Probabilistic Programs for Efficient Inference. - David Wingate; Noah D. Goodman; Andreas Stuhlmüller; Jeffrey Mark Siskind (NIPS, 2011)

Lightweight Implementations of Probabilistic Programming Languages Via Transformational Compilation. - David Wingate; Andreas Stuhlmüller; Noah D. Goodman (AISTATS, 2011)

Predictively Defined Representations of State. - David Wingate (Reinforcement Learning, 2012)

Automated Variational Inference in Probabilistic Programming - David Wingate; Theophane Weber (CoRR, 2013)

A Physics-Based Model Prior for Object-Oriented MDPs. - Jonathan Scholz; Martin Levihn; Charles Lee Isbell Jr.; David Wingate (ICML, 2014)

Directional NMF for joint source localization and separation. - Johannes Traa; Paris Smaragdis; Noah D. Stein; David Wingate (WASPAA, 2015)

Robust Source Localization and Enhancement With a Probabilistic Steered Response Power Model. - Johannes Traa; David Wingate; Noah D. Stein; Paris Smaragdis (IEEE ACM Trans. Audio Speech Lang. Process., 2016)

Harvesting Common-sense Navigational Knowledge for Robotics from Uncurated Text Corpora. - Nancy Fulda; Nathan Tibbetts; Zachary Brown 001; David Wingate (CoRL, 2017)

What Can You Do with a Rock? Affordance Extraction via Word Embeddings. - Nancy Fulda; Daniel Ricks; Ben Murdoch; David Wingate (IJCAI, 2017)

Deep visual gravity vector detection for unmanned aircraft attitude estimation. - Gary J. Ellingson; David Wingate; Timothy W. McLain (IROS, 2017)

Probabilistic programs for inferring the goals of autonomous agents. - Marco F. Cusumano-Towner; Alexey Radul; David Wingate; Vikash K. Mansinghka (CoRR, 2017)

Estimating Human Intent for Physical Human-Robot Co-Manipulation. - Eric C. Townsend; Erich A. Mielke; David Wingate; Marc D. Killpack (CoRR, 2017)

Threat, Explore, Barter, Puzzle: A Semantically-Informed Algorithm for Extracting Interaction Modes. - Nancy Fulda; Daniel Ricks; Ben Murdoch; David Wingate (AAAI Workshops, 2018)

Learning nonlinear dynamic models of soft robots for model predictive control with neural networks. - Morgan T. Gillespie; Charles M. Best; Eric C. Townsend; David Wingate; Marc D. Killpack (RoboSoft, 2018)

Embedding Grammars. - David Wingate; William Myers; Nancy Fulda; Tyler Etchart (CoRR, 2018)

Modeling Theory of Mind for Autonomous Agents with Probabilistic Programs. - Iris Rubi Seaman; Jan-Willem van de Meent; David Wingate (CoRR, 2018)

Graph Neural Processes: Towards Bayesian Graph Neural Networks. - Andrew N. Carr; David Wingate (CoRR, 2019)

Video Extrapolation with an Invertible Linear Embedding. - Robert Pottorff; Jared Nielsen; David Wingate (CoRR, 2019)

Wasserstein Neural Processes. - Andrew N. Carr; Jared Nielson; David Wingate (CoRR, 2019)

Using Logical Specifications of Objectives in Multi-Objective Reinforcement Learning. - Kolby Nottingham; Anand Balakrishnan 001; Jyotirmoy V. Deshmukh; Connor Christopherson; David Wingate (CoRR, 2019)

Model-Based Control of Soft Actuators Using Learned Non-linear Discrete-Time Models. - Phillip Hyatt; David Wingate; Marc D. Killpack (Frontiers Robotics AI, 2019)

Towards Neural Programming Interfaces. - Zachary Brown 001; Nathaniel R. Robinson; David Wingate; Nancy Fulda (NeurIPS, 2020)

Human-robot co-manipulation of extended objects: Data-driven models and control from analysis of human-human dyads. - Erich A. Mielke; Eric C. Townsend; David Wingate; Marc D. Killpack (CoRR, 2020)

Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning. - Christopher Michael Rytting; David Wingate (NeurIPS, 2021)

Using First Principles for Deep Learning and Model-Based Control of Soft Robots. - Curtis C. Johnson; Tyler Quackenbush; Taylor Sorensen; David Wingate; Marc D. Killpack (Frontiers Robotics AI, 2021)

An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels. - Taylor Sorensen; Joshua Robinson; Christopher Michael Rytting; Alexander Glenn Shaw; Kyle Jeffrey Rogers; Alexia Pauline Delorey; Mahmoud Khalil; Nancy Fulda; David Wingate (ACL (1), 2022)

Prompt Compression and Contrastive Conditioning for Controllability and Toxicity Reduction in Language Models. - David Wingate; Mohammad Shoeybi; Taylor Sorensen (EMNLP (Findings), 2022)

Out of One, Many: Using Language Models to Simulate Human Samples. - Lisa P. Argyle; Ethan C. Busby; Nancy Fulda; Joshua Gubler; Christopher Michael Rytting; David Wingate (CoRR, 2022)

Leveraging Large Language Models for Multiple Choice Question Answering. - Joshua Robinson; Christopher Michael Rytting; David Wingate (CoRR, 2022)

Leveraging Large Language Models for Multiple Choice Question Answering. - Joshua Robinson; David Wingate (ICLR, 2023)

AI Chat Assistants can Improve Conversations about Divisive Topics. - Lisa P. Argyle; Ethan C. Busby; Joshua Gubler; Chris Bail; Thomas Vin Howe; Christopher Michael Rytting; David Wingate (CoRR, 2023)

Towards Coding Social Science Datasets with Language Models. - Christopher Michael Rytting; Taylor Sorensen; Lisa P. Argyle; Ethan C. Busby; Nancy Fulda; Joshua Gubler; David Wingate (CoRR, 2023)

Human-robot planar co-manipulation of extended objects: data-driven models and control from human-human dyads. - Erich A. Mielke; Eric C. Townsend; David Wingate; John L. Salmon; Marc D. Killpack (Frontiers Neurorobotics, 2024)

Features that Make a Difference: Leveraging Gradients for Improved Dictionary Learning. - Jeffrey Olmo; Jared Wilson; Max Forsey; Bryce Hepner; Thomas Vin Howe; David Wingate (NAACL (Findings), 2025)

Arti-"fickle" Intelligence: Using LLMs as a Tool for Inference in the Political and Social Sciences. - Lisa P. Argyle; Ethan C. Busby; Joshua Gubler; Bryce Hepner; Alex Lyman; David Wingate (CoRR, 2025)