David Wingate - RankMe

68 papers A* 13A 7C 2Misc 1Journal 30Unranked 13

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Arti-"fickle" Intelligence: Using LLMs as a Tool for Inference in the Political and Social Sciences. CoRR Lisa P. Argyle, Ethan C. Busby, Joshua Gubler, Bryce Hepner, Alex Lyman, David Wingate
2025	J	`jnl`	Arti-'fickle' intelligence: using LLMs as a tool for inference in the political and social sciences. Nat. Comput. Sci. Lisa P. Argyle, Ethan C. Busby, Joshua Gubler, Bryce Hepner, Alex Lyman, David Wingate
2025	—	`conf`	Features that Make a Difference: Leveraging Gradients for Improved Dictionary Learning. NAACL (Findings) Jeffrey Olmo, Jared Wilson, Max Forsey, Bryce Hepner, Thomas Vin Howe, David Wingate
2024	J	`jnl`	Features that Make a Difference: Leveraging Gradients for Improved Dictionary Learning. CoRR Jeffrey Olmo, Jared Wilson, Max Forsey, Bryce Hepner, Thomas Vin Howe, David Wingate
2024	J	`jnl`	Human-robot planar co-manipulation of extended objects: data-driven models and control from human-human dyads. Frontiers Neurorobotics Erich A. Mielke, Eric C. Townsend, David Wingate, John L. Salmon, Marc D. Killpack
2023	J	`jnl`	AI Chat Assistants can Improve Conversations about Divisive Topics. CoRR Lisa P. Argyle, Ethan C. Busby, Joshua Gubler, Chris Bail, Thomas Vin Howe, Christopher Michael Rytting, David Wingate
2023	A*	`conf`	Leveraging Large Language Models for Multiple Choice Question Answering. ICLR Joshua Robinson, David Wingate
2023	J	`jnl`	Towards Coding Social Science Datasets with Language Models. CoRR Christopher Michael Rytting, Taylor Sorensen, Lisa P. Argyle, Ethan C. Busby, Nancy Fulda, Joshua Gubler, David Wingate
2022	—	`conf`	An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels. ACL (1) Taylor Sorensen, Joshua Robinson, Christopher Michael Rytting, Alexander Glenn Shaw, Kyle Jeffrey Rogers, Alexia Pauline Delorey, Mahmoud Khalil, Nancy Fulda, David Wingate
2022	J	`jnl`	An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels. CoRR Taylor Sorensen, Joshua Robinson, Christopher Michael Rytting, Alexander Glenn Shaw, Kyle Jeffrey Rogers, Alexia Pauline Delorey, Mahmoud Khalil, Nancy Fulda, David Wingate
2022	J	`jnl`	Leveraging Large Language Models for Multiple Choice Question Answering. CoRR Joshua Robinson, Christopher Michael Rytting, David Wingate
2022	J	`jnl`	Out of One, Many: Using Language Models to Simulate Human Samples. CoRR Lisa P. Argyle, Ethan C. Busby, Nancy Fulda, Joshua Gubler, Christopher Michael Rytting, David Wingate
2022	—	`conf`	Prompt Compression and Contrastive Conditioning for Controllability and Toxicity Reduction in Language Models. EMNLP (Findings) David Wingate, Mohammad Shoeybi, Taylor Sorensen
2022	J	`jnl`	Prompt Compression and Contrastive Conditioning for Controllability and Toxicity Reduction in Language Models. CoRR David Wingate, Mohammad Shoeybi, Taylor Sorensen
2021	A*	`conf`	Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning. NeurIPS Christopher Michael Rytting, David Wingate
2021	J	`jnl`	Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning. CoRR Christopher Michael Rytting, David Wingate
2021	J	`jnl`	Using First Principles for Deep Learning and Model-Based Control of Soft Robots. Frontiers Robotics AI Curtis C. Johnson, Tyler Quackenbush, Taylor Sorensen, David Wingate, Marc D. Killpack
2020	J	`jnl`	Human-robot co-manipulation of extended objects: Data-driven models and control from analysis of human-human dyads. CoRR Erich A. Mielke, Eric C. Townsend, David Wingate, Marc D. Killpack
2020	A*	`conf`	Towards Neural Programming Interfaces. NeurIPS Zachary Brown, Nathaniel R. Robinson, David Wingate, Nancy Fulda
2020	J	`jnl`	Towards Neural Programming Interfaces. CoRR Zachary C. Brown, Nathaniel R. Robinson, David Wingate, Nancy Fulda
2019	J	`jnl`	Graph Neural Processes: Towards Bayesian Graph Neural Networks. CoRR Andrew N. Carr, David Wingate
2019	J	`jnl`	Model-Based Control of Soft Actuators Using Learned Non-linear Discrete-Time Models. Frontiers Robotics AI Phillip Hyatt, David Wingate, Marc D. Killpack
2019	J	`jnl`	Using Logical Specifications of Objectives in Multi-Objective Reinforcement Learning. CoRR Kolby Nottingham, Anand Balakrishnan, Jyotirmoy V. Deshmukh, Connor Christopherson, David Wingate
2019	J	`jnl`	Video Extrapolation with an Invertible Linear Embedding. CoRR Robert Pottorff, Jared Nielsen, David Wingate
2019	J	`jnl`	Wasserstein Neural Processes. CoRR Andrew N. Carr, Jared Nielson, David Wingate
2018	J	`jnl`	Embedding Grammars. CoRR David Wingate, William Myers, Nancy Fulda, Tyler Etchart
2018	—	`conf`	Learning nonlinear dynamic models of soft robots for model predictive control with neural networks. RoboSoft Morgan T. Gillespie, Charles M. Best, Eric C. Townsend, David Wingate, Marc D. Killpack
2018	J	`jnl`	Modeling Theory of Mind for Autonomous Agents with Probabilistic Programs. CoRR Iris Rubi Seaman, Jan-Willem van de Meent, David Wingate
2018	—	`conf`	Threat, Explore, Barter, Puzzle: A Semantically-Informed Algorithm for Extracting Interaction Modes. AAAI Workshops Nancy Fulda, Daniel Ricks, Ben Murdoch, David Wingate
2017	A	`conf`	Deep visual gravity vector detection for unmanned aircraft attitude estimation. IROS Gary J. Ellingson, David Wingate, Timothy W. McLain
2017	J	`jnl`	Estimating Human Intent for Physical Human-Robot Co-Manipulation. CoRR Eric C. Townsend, Erich A. Mielke, David Wingate, Marc D. Killpack
2017	Misc	`conf`	Harvesting Common-sense Navigational Knowledge for Robotics from Uncurated Text Corpora. CoRL Nancy Fulda, Nathan Tibbetts, Zachary Brown, David Wingate
2017	J	`jnl`	Probabilistic programs for inferring the goals of autonomous agents. CoRR Marco F. Cusumano-Towner, Alexey Radul, David Wingate, Vikash K. Mansinghka
2017	A*	`conf`	What Can You Do with a Rock? Affordance Extraction via Word Embeddings. IJCAI Nancy Fulda, Daniel Ricks, Ben Murdoch, David Wingate
2017	J	`jnl`	What can you do with a rock? Affordance extraction via word embeddings. CoRR Nancy Fulda, Daniel Ricks, Ben Murdoch, David Wingate
2016	J	`jnl`	Robust Source Localization and Enhancement With a Probabilistic Steered Response Power Model. IEEE ACM Trans. Audio Speech Lang. Process. Johannes Traa, David Wingate, Noah D. Stein, Paris Smaragdis
2015	—	`conf`	Directional NMF for joint source localization and separation. WASPAA Johannes Traa, Paris Smaragdis, Noah D. Stein, David Wingate
2014	A*	`conf`	A Physics-Based Model Prior for Object-Oriented MDPs. ICML Jonathan Scholz, Martin Levihn, Charles Lee Isbell Jr., David Wingate
2013	J	`jnl`	Automated Variational Inference in Probabilistic Programming CoRR David Wingate, Theophane Weber
2012	J	`jnl`	A Bayesian Sampling Approach to Exploration in Reinforcement Learning CoRR John Asmuth, Lihong Li, Michael L. Littman, Ali Nouri, David Wingate
2012	J	`jnl`	Predictive Linear-Gaussian Models of Stochastic Dynamical Systems CoRR Matthew R. Rudary, Satinder Singh, David Wingate
2012	—	`ch.`	Predictively Defined Representations of State. Reinforcement Learning David Wingate
2012	J	`jnl`	The Infinite Latent Events Model CoRR David Wingate, Noah D. Goodman, Daniel M. Roy, Joshua B. Tenenbaum
2011	—	`conf`	An expanding reference library for Peer-to-Peer content. eCrime Researchers Summit Jason Valdez, Mina Guirguis, David Wingate, Rory Rinkevich
2011	A*	`conf`	Bayesian Policy Search with Policy Priors. IJCAI David Wingate, Noah D. Goodman, Daniel M. Roy, Leslie Pack Kaelbling, Joshua B. Tenenbaum
2011	A*	`conf`	Infinite Dynamic Bayesian Networks. ICML Finale Doshi, David Wingate, Joshua B. Tenenbaum, Nicholas Roy
2011	A	`conf`	Lightweight Implementations of Probabilistic Programming Languages Via Transformational Compilation. AISTATS David Wingate, Andreas Stuhlmüller, Noah D. Goodman
2011	—	`conf`	Nonstandard Interpretations of Probabilistic Programs for Efficient Inference. NIPS David Wingate, Noah D. Goodman, Andreas Stuhlmüller, Jeffrey Mark Siskind
2011	—	`conf`	Smart data structures: an online machine learning approach to multicore data structures. ICAC Jonathan Eastep, David Wingate, Anant Agarwal
2010	—	`conf`	Nonparametric Bayesian Policy Priors for Reinforcement Learning. NIPS Finale Doshi-Velez, David Wingate, Nicholas Roy, Joshua B. Tenenbaum
2010	—	`conf`	Smartlocks: lock acquisition scheduling for self-aware synchronization. ICAC Jonathan Eastep, David Wingate, Marco D. Santambrogio, Anant Agarwal
2009	A	`conf`	A Bayesian Sampling Approach to Exploration in Reinforcement Learning. UAI John Asmuth, Lihong Li, Michael L. Littman, Ali Nouri, David Wingate
2009	A	`conf`	The Infinite Latent Events Model. UAI David Wingate, Noah D. Goodman, Daniel M. Roy, Joshua B. Tenenbaum
2009	A*	`conf`	Workshop summary: Results of the 2009 reinforcement learning competition. ICML David Wingate, Carlos Diuk, Lihong Li, Matthew Taylor, Jordan Frank
2008	A*	`conf`	Efficiently learning linear-linear exponential family predictive representations of state. ICML David Wingate, Satinder Singh
2008	—	`—`	Exponential Family Predictive Representations of State. David Wingate
2008	—	`conf`	Sigma point policy iteration. AAMAS (1) Michael H. Bowling, Alborz Geramifard, David Wingate
2007	—	`conf`	Exponential Family Predictive Representations of State. NIPS David Wingate, Satinder Singh
2007	A	`conf`	On discovery and learning of models with predictive representations of state for agents with continuous actions and observations. AAMAS David Wingate, Satinder Singh
2007	A*	`conf`	Relational Knowledge with Predictive State Representations. IJCAI David Wingate, Vishal Soni, Britton Wolfe, Satinder Singh
2006	A*	`conf`	Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems. ICML David Wingate, Satinder Singh
2006	A*	`conf`	Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems. AAAI David Wingate, Satinder Singh
2005	A	`conf`	Predictive Linear-Gaussian Models of Stochastic Dynamical Systems. UAI Matthew R. Rudary, Satinder Singh, David Wingate
2005	J	`jnl`	Prioritization Methods for Accelerating MDP Solvers. J. Mach. Learn. Res. David Wingate, Kevin D. Seppi
2005	A	`conf`	Prioritized Multiplicative Schwarz Procedures for Solving Linear Systems. IPDPS David Wingate, Nathaniel Powell, Quinn Snell, Kevin D. Seppi
2004	A*	`conf`	P3VI: a partitioned, prioritized, parallel value iterator. ICML David Wingate, Kevin D. Seppi
2004	C	`conf`	Variable resolution discretization in the joint space. ICMLA Christopher K. Monson, David Wingate, Kevin D. Seppi, Todd S. Peterson
2003	C	`conf`	Efficient Value Iteration Using Partitioned Models. ICMLA David Wingate, Kevin D. Seppi