David Wingate

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 33

Top Topics

Source Localization

Ground Truth Labels

Top Venues

Frontiers Robotics AI

Publications

Erich A. Mielke, Eric C. Townsend, David Wingate, John L. Salmon, Marc D. Killpack
Human-robot planar co-manipulation of extended objects: data-driven models and control from human-human dyads. Frontiers Neurorobotics 18 (2024)
Christopher Michael Rytting, Taylor Sorensen, Lisa P. Argyle, Ethan C. Busby, Nancy Fulda, Joshua Gubler, David Wingate
Towards Coding Social Science Datasets with Language Models. CoRR (2023)
Lisa P. Argyle, Ethan C. Busby, Joshua Gubler, Chris Bail, Thomas Howe, Christopher Michael Rytting, David Wingate
AI Chat Assistants can Improve Conversations about Divisive Topics. CoRR (2023)
Joshua Robinson, David Wingate
Leveraging Large Language Models for Multiple Choice Question Answering. ICLR (2023)
Joshua Robinson, Christopher Michael Rytting, David Wingate
Leveraging Large Language Models for Multiple Choice Question Answering. CoRR (2022)
David Wingate, Mohammad Shoeybi, Taylor Sorensen
Prompt Compression and Contrastive Conditioning for Controllability and Toxicity Reduction in Language Models. CoRR (2022)
Lisa P. Argyle, Ethan C. Busby, Nancy Fulda, Joshua Gubler, Christopher Michael Rytting, David Wingate
Out of One, Many: Using Language Models to Simulate Human Samples. CoRR (2022)
David Wingate, Mohammad Shoeybi, Taylor Sorensen
Prompt Compression and Contrastive Conditioning for Controllability and Toxicity Reduction in Language Models. EMNLP (Findings) (2022)
Taylor Sorensen, Joshua Robinson, Christopher Michael Rytting, Alexander Glenn Shaw, Kyle Jeffrey Rogers, Alexia Pauline Delorey, Mahmoud Khalil, Nancy Fulda, David Wingate
An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels. ACL (1) (2022)
Taylor Sorensen, Joshua Robinson, Christopher Michael Rytting, Alexander Glenn Shaw, Kyle Jeffrey Rogers, Alexia Pauline Delorey, Mahmoud Khalil, Nancy Fulda, David Wingate
An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels. CoRR (2022)
Curtis C. Johnson, Tyler Quackenbush, Taylor Sorensen, David Wingate, Marc D. Killpack
Using First Principles for Deep Learning and Model-Based Control of Soft Robots. Frontiers Robotics AI 8 (2021)
Christopher Michael Rytting, David Wingate
Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning. CoRR (2021)
Christopher Michael Rytting, David Wingate
Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning. NeurIPS (2021)
Zachary C. Brown, Nathaniel Robinson, David Wingate, Nancy Fulda
Towards Neural Programming Interfaces. CoRR (2020)
Erich A. Mielke, Eric C. Townsend, David Wingate, Marc D. Killpack
Human-robot co-manipulation of extended objects: Data-driven models and control from analysis of human-human dyads. CoRR (2020)
Zachary Brown, Nathaniel Robinson, David Wingate, Nancy Fulda
Towards Neural Programming Interfaces. NeurIPS (2020)
Robert Pottorff, Jared Nielsen, David Wingate
Video Extrapolation with an Invertible Linear Embedding. CoRR (2019)
Andrew N. Carr, David Wingate
Graph Neural Processes: Towards Bayesian Graph Neural Networks. CoRR (2019)
Kolby Nottingham, Anand Balakrishnan, Jyotirmoy V. Deshmukh, Connor Christopherson, David Wingate
Using Logical Specifications of Objectives in Multi-Objective Reinforcement Learning. CoRR (2019)
Andrew N. Carr, Jared Nielson, David Wingate
Wasserstein Neural Processes. CoRR (2019)
Phillip Hyatt, David Wingate, Marc D. Killpack
Model-Based Control of Soft Actuators Using Learned Non-linear Discrete-Time Models. Frontiers Robotics AI 6 (2019)
David Wingate, William Myers, Nancy Fulda, Tyler Etchart
Embedding Grammars. CoRR (2018)
Nancy Fulda, Daniel Ricks, Ben Murdoch, David Wingate
Threat, Explore, Barter, Puzzle: A Semantically-Informed Algorithm for Extracting Interaction Modes. AAAI Workshops (2018)
Morgan T. Gillespie, Charles M. Best, Eric C. Townsend, David Wingate, Marc D. Killpack
Learning nonlinear dynamic models of soft robots for model predictive control with neural networks. RoboSoft (2018)
Iris Rubi Seaman, Jan-Willem van de Meent, David Wingate
Modeling Theory of Mind for Autonomous Agents with Probabilistic Programs. CoRR (2018)
Nancy Fulda, Daniel Ricks, Ben Murdoch, David Wingate
What can you do with a rock? Affordance extraction via word embeddings. CoRR (2017)
Nancy Fulda, Daniel Ricks, Ben Murdoch, David Wingate
What Can You Do with a Rock? Affordance Extraction via Word Embeddings. IJCAI (2017)
Nancy Fulda, Nathan Tibbetts, Zachary Brown, David Wingate
Harvesting Common-sense Navigational Knowledge for Robotics from Uncurated Text Corpora. CoRL (2017)
Gary J. Ellingson, David Wingate, Timothy W. McLain
Deep visual gravity vector detection for unmanned aircraft attitude estimation. IROS (2017)
Marco F. Cusumano-Towner, Alexey Radul, David Wingate, Vikash K. Mansinghka
Probabilistic programs for inferring the goals of autonomous agents. CoRR (2017)
Eric C. Townsend, Erich A. Mielke, David Wingate, Marc D. Killpack
Estimating Human Intent for Physical Human-Robot Co-Manipulation. CoRR (2017)
Johannes Traa, David Wingate, Noah D. Stein, Paris Smaragdis
Robust Source Localization and Enhancement With a Probabilistic Steered Response Power Model. IEEE ACM Trans. Audio Speech Lang. Process. 24 (3) (2016)
Johannes Traa, Paris Smaragdis, Noah D. Stein, David Wingate
Directional NMF for joint source localization and separation. WASPAA (2015)
Jonathan Scholz, Martin Levihn, Charles Lee Isbell Jr., David Wingate
A Physics-Based Model Prior for Object-Oriented MDPs. ICML (2014)
David Wingate, Theophane Weber
Automated Variational Inference in Probabilistic Programming CoRR (2013)
John Asmuth, Lihong Li, Michael L. Littman, Ali Nouri, David Wingate
A Bayesian Sampling Approach to Exploration in Reinforcement Learning CoRR (2012)
David Wingate, Noah D. Goodman, Daniel M. Roy, Joshua B. Tenenbaum
The Infinite Latent Events Model CoRR (2012)
Matthew R. Rudary, Satinder P. Singh, David Wingate
Predictive Linear-Gaussian Models of Stochastic Dynamical Systems CoRR (2012)
David Wingate, Andreas Stuhlmüller, Noah D. Goodman
Lightweight Implementations of Probabilistic Programming Languages Via Transformational Compilation. AISTATS (2011)
David Wingate, Noah D. Goodman, Andreas Stuhlmüller, Jeffrey Mark Siskind
Nonstandard Interpretations of Probabilistic Programs for Efficient Inference. NIPS (2011)
Jason Valdez, Mina Guirguis, David Wingate, Rory Rinkevich
An expanding reference library for Peer-to-Peer content. eCrime Researchers Summit (2011)
Finale Doshi, David Wingate, Joshua B. Tenenbaum, Nicholas Roy
Infinite Dynamic Bayesian Networks. ICML (2011)
David Wingate, Noah D. Goodman, Daniel M. Roy, Leslie Pack Kaelbling, Joshua B. Tenenbaum
Bayesian Policy Search with Policy Priors. IJCAI (2011)
Jonathan Eastep, David Wingate, Anant Agarwal
Smart data structures: an online machine learning approach to multicore data structures. ICAC (2011)
Finale Doshi-Velez, David Wingate, Nicholas Roy, Joshua B. Tenenbaum
Nonparametric Bayesian Policy Priors for Reinforcement Learning. NIPS (2010)
Jonathan Eastep, David Wingate, Marco D. Santambrogio, Anant Agarwal
Smartlocks: lock acquisition scheduling for self-aware synchronization. ICAC (2010)
David Wingate, Carlos Diuk, Lihong Li, Matthew Taylor, Jordan Frank
Workshop summary: Results of the 2009 reinforcement learning competition. ICML (2009)
David Wingate, Noah D. Goodman, Daniel M. Roy, Joshua B. Tenenbaum
The Infinite Latent Events Model. UAI (2009)
John Asmuth, Lihong Li, Michael L. Littman, Ali Nouri, David Wingate
A Bayesian Sampling Approach to Exploration in Reinforcement Learning. UAI (2009)
David Wingate, Satinder P. Singh
Efficiently learning linear-linear exponential family predictive representations of state. ICML (2008)
Michael H. Bowling, Alborz Geramifard, David Wingate
Sigma point policy iteration. AAMAS (1) (2008)
David Wingate, Satinder Singh (Baveja)
Exponential Family Predictive Representations of State. NIPS (2007)
David Wingate, Vishal Soni, Britton Wolfe, Satinder P. Singh
Relational Knowledge with Predictive State Representations. IJCAI (2007)
David Wingate, Satinder P. Singh
On discovery and learning of models with predictive representations of state for agents with continuous actions and observations. AAMAS (2007)
David Wingate, Satinder P. Singh
Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems. AAAI (2006)
David Wingate, Satinder P. Singh
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems. ICML (2006)
David Wingate, Kevin D. Seppi
Prioritization Methods for Accelerating MDP Solvers. J. Mach. Learn. Res. 6 (2005)
Matthew R. Rudary, Satinder P. Singh, David Wingate
Predictive Linear-Gaussian Models of Stochastic Dynamical Systems. UAI (2005)
David Wingate, Nathaniel Powell, Quinn Snell, Kevin D. Seppi
Prioritized Multiplicative Schwarz Procedures for Solving Linear Systems. IPDPS (2005)
David Wingate, Kevin D. Seppi
P3VI: a partitioned, prioritized, parallel value iterator. ICML (2004)
Christopher K. Monson, David Wingate, Kevin D. Seppi, Todd S. Peterson
Variable resolution discretization in the joint space. ICMLA (2004)
David Wingate, Kevin D. Seppi
Efficient Value Iteration Using Partitioned Models. ICMLA (2003)