David Wingate

发表

Predictively Defined Representations of State

David Wingate, D. Wingate, 2012, Reinforcement Learning.

Sigma point policy iteration

Alborz Geramifard, Michael H. Bowling, David Wingate, 2008, AAMAS.

Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems

Satinder P. Singh, David Wingate, 2006, AAAI.

Workshop summary: Results of the 2009 reinforcement learning competition

Lihong Li, Matthew Taylor, David Wingate, 2009, ICML '09.

Scalable Probabilistic Programming for Learning and Acting in Complex Domains

David Wingate, 2019 .

An expanding reference library for Peer-to-Peer content

Mina Guirguis, David Wingate, Jason Valdez, 2011, 2011 eCrime Researchers Summit.

Video Extrapolation with an Invertible Linear Embedding pdf

David Wingate, Robert Pottorff, Jared Nielsen, 2019, ArXiv.

Efficiently learning linear-linear exponential family predictive representations of state

Satinder P. Singh, David Wingate, 2008, ICML '08.

Exponential Family Predictive Representations of State

Satinder P. Singh, David Wingate, Satinder Singh, 2007, NIPS.

Graph Neural Processes: Towards Bayesian Graph Neural Networks pdf

David Wingate, Andrew N. Carr, Andrew N. Carr, 2019, ArXiv.

P3VI: a partitioned, prioritized, parallel value iterator

Kevin D. Seppi, David Wingate, D. Wingate, 2004, ICML.

Using Logical Specifications of Objectives in Multi-Objective Reinforcement Learning pdf

David Wingate, Kolby Nottingham, Anand Balakrishnan, 2019, ArXiv.

Designing intelligent robots : reintegrating AI : papers from the AAAI Spring Symposium

Byron Boots, George Konidaris, Benjamin Rosman, 2012 .

Lightweight Implementations of Probabilistic Programming Languages Via Transformational Compilation

Noah D. Goodman, David Wingate, Andreas Stuhlmüller, 2011, AISTATS.

Learning nonlinear dynamic models of soft robots for model predictive control with neural networks

David Wingate, Marc D. Killpack, Charles M. Best, 2018, 2018 IEEE International Conference on Soft Robotics (RoboSoft).

Directional NMF for joint source localization and separation

Paris Smaragdis, Noah D. Stein, David Wingate, 2015, 2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA).

A Physics-Based Model Prior for Object-Oriented MDPs

David Wingate, Charles Lee Isbell, Jonathan Scholz, 2014, ICML.

Embedding Grammars pdf

David Wingate, William Myers, Nancy Fulda, 2018, ArXiv.

Prioritization Methods for Accelerating MDP Solvers

Kevin D. Seppi, David Wingate, D. Wingate, 2005, J. Mach. Learn. Res..

Human-robot co-manipulation of extended objects: Data-driven models and control from analysis of human-human dyads pdf

David Wingate, Marc D. Killpack, Erich Mielke, 2020, ArXiv.

Smartlocks: lock acquisition scheduling for self-aware synchronization

Anant Agarwal, Marco D. Santambrogio, David Wingate, 2010, ICAC '10.

Solving Large MDPs Quickly with Partitioned Value Iteration

David Wingate, 2004 .

Nonparametric Bayesian Policy Priors for Reinforcement Learning

Joshua B. Tenenbaum, Nicholas Roy, Finale Doshi-Velez, 2010, NIPS.

Infinite Dynamic Bayesian Networks

Joshua B. Tenenbaum, Nicholas Roy, Finale Doshi-Velez, 2011, ICML.

Deep visual gravity vector detection for unmanned aircraft attitude estimation

David Wingate, Tim McLain, Gary Ellingson, 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Automated Variational Inference in Probabilistic Programming pdf

David Wingate, Theophane Weber, T. Weber, 2013, ArXiv.

Probabilistic programs for inferring the goals of autonomous agents pdf

Vikash K. Mansinghka, David Wingate, Alexey Radul, 2017, ArXiv.

Prioritized multiplicative Schwarz procedures for solving linear systems

Quinn Snell, Kevin D. Seppi, David Wingate, 2005, 19th IEEE International Parallel and Distributed Processing Symposium.

Towards Neural Programming Interfaces pdf

David Wingate, Nancy Fulda, Nathaniel Robinson, 2020, NeurIPS.

Efficient Value Iteration Using Partitioned Models

Kevin D. Seppi, David Wingate, 2003, ICMLA.

ProSPr: Democratized Implementation of Alphafold Protein Distance Prediction Network

David Wingate, Dennis Della Corte, Wendy M. Billings, 2019, bioRxiv.

Relational Knowledge with Predictive State Representations

Vishal Soni, Satinder P. Singh, Britton Wolfe, 2007, IJCAI.

Acquiring and Exploiting Rich Causal Models for Robust Decision Making

Leslie Pack Kaelbling, Joshua B. Tenenbaum, Michael L. Littman, 2012 .

On discovery and learning of models with predictive representations of state for agents with continuous actions and observations

Satinder P. Singh, David Wingate, Satinder Singh, 2007, AAMAS '07.

Harvesting Common-sense Navigational Knowledge for Robotics from Uncurated Text Corpora

David Wingate, Nancy Fulda, Zachary Brown, 2017, CoRL.

Smartlocks: Self-Aware Synchronization through Lock Acquisition Scheduling

Anant Agarwal, Marco D. Santambrogio, David Wingate, 2009 .

Robust Source Localization and Enhancement With a Probabilistic Steered Response Power Model

Paris Smaragdis, Noah D. Stein, David Wingate, 2016, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

A Bayesian Sampling Approach to Exploration in Reinforcement Learning pdf

Lihong Li, Michael L. Littman, David Wingate, 2009, UAI.

What Can You Do with a Rock? Affordance Extraction via Word Embeddings

David Wingate, Nancy Fulda, Daniel Ricks, 2017, IJCAI.

Threat, Explore, Barter, Puzzle: A Semantically-Informed Algorithm for Extracting Interaction Modes

David Wingate, Nancy Fulda, Daniel Ricks, 2018, AAAI Workshops.

Variable resolution discretization in the joint space

Kevin D. Seppi, David Wingate, Christopher K. Monson, 2004, 2004 International Conference on Machine Learning and Applications, 2004. Proceedings..

The Infinite Latent Events Model

Joshua B. Tenenbaum, Noah D. Goodman, Daniel M. Roy, 2009, UAI.

Estimating Human Intent for Physical Human-Robot Co-Manipulation pdf

David Wingate, Marc D. Killpack, Eric C. Townsend, 2017, ArXiv.

Nested Reasoning About Autonomous Agents Using Probabilistic Programs

Jan-Willem van de Meent, David Wingate, Iris Rubi Seaman, 2018 .

Wasserstein Neural Processes pdf

David Wingate, Andrew Carr, Jared Nielson, 2019, ArXiv.

Bayesian Policy Search with Policy Priors

Leslie Pack Kaelbling, Joshua B. Tenenbaum, Noah D. Goodman, 2011, IJCAI.

Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems

Satinder P. Singh, David Wingate, Satinder Singh, 2006, ICML.

Predictive Linear-Gaussian Models of Stochastic Dynamical Systems

Satinder P. Singh, David Wingate, Matthew R. Rudary, 2005, UAI.

Nonstandard Interpretations of Probabilistic Programs for Efficient Inference

Noah D. Goodman, Jeffrey Mark Siskind, David Wingate, 2011, NIPS.

Model-Based Control of Soft Actuators Using Learned Non-linear Discrete-Time Models

David Wingate, Marc D. Killpack, Phillip Hyatt, 2019, Front. Robot. AI.

Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning pdf

David Wingate, Christopher Michael Rytting, D. Wingate, 2021, NeurIPS.

Using First Principles for Deep Learning and Model-Based Control of Soft Robots

David Wingate, Marc D. Killpack, Curtis C. Johnson, 2021, Frontiers in Robotics and AI.

PAC-MDP Reinforcement Learning with Bayesian Priors

Michael L. Littman, David Wingate, Ali Nouri, 2009 .