David Wingate

According to our database1, David Wingate authored at least 55 papers between 2003 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2023
Towards Coding Social Science Datasets with Language Models.
CoRR, 2023

AI Chat Assistants can Improve Conversations about Divisive Topics.
CoRR, 2023

Leveraging Large Language Models for Multiple Choice Question Answering.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Leveraging Large Language Models for Multiple Choice Question Answering.
CoRR, 2022

Out of One, Many: Using Language Models to Simulate Human Samples.
CoRR, 2022

Prompt Compression and Contrastive Conditioning for Controllability and Toxicity Reduction in Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
Using First Principles for Deep Learning and Model-Based Control of Soft Robots.
Frontiers Robotics AI, 2021

Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Human-robot co-manipulation of extended objects: Data-driven models and control from analysis of human-human dyads.
CoRR, 2020

Towards Neural Programming Interfaces.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Model-Based Control of Soft Actuators Using Learned Non-linear Discrete-Time Models.
Frontiers Robotics AI, 2019

Using Logical Specifications of Objectives in Multi-Objective Reinforcement Learning.
CoRR, 2019

Wasserstein Neural Processes.
CoRR, 2019

Video Extrapolation with an Invertible Linear Embedding.
CoRR, 2019

Graph Neural Processes: Towards Bayesian Graph Neural Networks.
CoRR, 2019

2018
Modeling Theory of Mind for Autonomous Agents with Probabilistic Programs.
CoRR, 2018

Embedding Grammars.
CoRR, 2018

Learning nonlinear dynamic models of soft robots for model predictive control with neural networks.
Proceedings of the IEEE International Conference on Soft Robotics, 2018

Threat, Explore, Barter, Puzzle: A Semantically-Informed Algorithm for Extracting Interaction Modes.
Proceedings of the Workshops of the The Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Estimating Human Intent for Physical Human-Robot Co-Manipulation.
CoRR, 2017

Probabilistic programs for inferring the goals of autonomous agents.
CoRR, 2017

Deep visual gravity vector detection for unmanned aircraft attitude estimation.
Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

What Can You Do with a Rock? Affordance Extraction via Word Embeddings.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Harvesting Common-sense Navigational Knowledge for Robotics from Uncurated Text Corpora.
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

2016
Robust Source Localization and Enhancement With a Probabilistic Steered Response Power Model.
IEEE ACM Trans. Audio Speech Lang. Process., 2016

2015
Directional NMF for joint source localization and separation.
Proceedings of the 2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2015

2014
A Physics-Based Model Prior for Object-Oriented MDPs.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
Automated Variational Inference in Probabilistic Programming
CoRR, 2013

2012
Predictively Defined Representations of State.
Proceedings of the Reinforcement Learning, 2012

2011
Lightweight Implementations of Probabilistic Programming Languages Via Transformational Compilation.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Nonstandard Interpretations of Probabilistic Programs for Efficient Inference.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Bayesian Policy Search with Policy Priors.
Proceedings of the IJCAI 2011, 2011

Infinite Dynamic Bayesian Networks.
Proceedings of the 28th International Conference on Machine Learning, 2011

Smart data structures: an online machine learning approach to multicore data structures.
Proceedings of the 8th International Conference on Autonomic Computing, 2011

An expanding reference library for Peer-to-Peer content.
Proceedings of the 2011 eCrime Researchers Summit, 2011

2010
Nonparametric Bayesian Policy Priors for Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Smartlocks: lock acquisition scheduling for self-aware synchronization.
Proceedings of the 7th International Conference on Autonomic Computing, 2010

2009
The Infinite Latent Events Model.
Proceedings of the UAI 2009, 2009

A Bayesian Sampling Approach to Exploration in Reinforcement Learning.
Proceedings of the UAI 2009, 2009

Workshop summary: Results of the 2009 reinforcement learning competition.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Exponential Family Predictive Representations of State.
PhD thesis, 2008

Efficiently learning linear-linear exponential family predictive representations of state.
Proceedings of the Machine Learning, 2008

Sigma point policy iteration.
Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), 2008

2007
Exponential Family Predictive Representations of State.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Relational Knowledge with Predictive State Representations.
Proceedings of the IJCAI 2007, 2007

On discovery and learning of models with predictive representations of state for agents with continuous actions and observations.
Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2007), 2007

2006
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems.
Proceedings of the Machine Learning, 2006

Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems.
Proceedings of the Proceedings, 2006

2005
Prioritization Methods for Accelerating MDP Solvers.
J. Mach. Learn. Res., 2005

Predictive Linear-Gaussian Models of Stochastic Dynamical Systems.
Proceedings of the UAI '05, 2005

Prioritized Multiplicative Schwarz Procedures for Solving Linear Systems.
Proceedings of the 19th International Parallel and Distributed Processing Symposium (IPDPS 2005), 2005

2004
Variable resolution discretization in the joint space.
Proceedings of the 2004 International Conference on Machine Learning and Applications, 2004

P3VI: a partitioned, prioritized, parallel value iterator.
Proceedings of the Machine Learning, 2004

2003
Efficient Value Iteration Using Partitioned Models.
Proceedings of the 2003 International Conference on Machine Learning and Applications, 2003


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