David Wingate
Title
Cited by
Cited by
Year
Lightweight implementations of probabilistic programming languages via transformational compilation
D Wingate, A Stuhlmüller, N Goodman
Proceedings of the Fourteenth International Conference on Artificial …, 2011
1792011
A Bayesian sampling approach to exploration in reinforcement learning
J Asmuth, L Li, ML Littman, A Nouri, D Wingate
arXiv preprint arXiv:1205.2664, 2012
1772012
Automated variational inference in probabilistic programming
D Wingate, T Weber
arXiv preprint arXiv:1301.1299, 2013
1032013
Prioritization Methods for Accelerating MDP Solvers.
D Wingate, KD Seppi, S Mahadevan
Journal of Machine Learning Research 6 (5), 2005
1022005
Acoustic source tracking and selection
D Wingate, ND Stein, B Vigoda, P Ohiomoba, B Donnelly
US Patent App. 14/847,818, 2016
732016
What can you do with a rock? affordance extraction via word embeddings
N Fulda, D Ricks, B Murdoch, D Wingate
arXiv preprint arXiv:1703.03429, 2017
662017
A physics-based model prior for object-oriented mdps
J Scholz, M Levihn, C Isbell, D Wingate
International Conference on Machine Learning, 1089-1097, 2014
532014
Learning nonlinear dynamic models of soft robots for model predictive control with neural networks
MT Gillespie, CM Best, EC Townsend, D Wingate, MD Killpack
2018 IEEE International Conference on Soft Robotics (RoboSoft), 39-45, 2018
442018
Nonparametric Bayesian policy priors for reinforcement learning
F Doshi-Velez, D Wingate, N Roy, J Tenenbaum
Neural Information Processing Systems Foundation, 2010
432010
Infinite dynamic Bayesian networks
F Doshi, D Wingate, JB Tenenbaum, N Roy
ICML, 2011
402011
Machine-learned multi-system surrogate models for materials prediction
C Nyshadham, M Rupp, B Bekker, AV Shapeev, T Mueller, ...
npj Computational Materials 5 (1), 1-6, 2019
362019
Nonstandard interpretations of probabilistic programs for efficient inference
D Wingate, N Goodman, A Stuhlmüller, JM Siskind
Advances in Neural Information Processing Systems, 1152-1160, 2011
362011
Bayesian policy search with policy priors
D Wingate, ND Goodman, DM Roy, LP Kaelbling, JB Tenenbaum
Twenty-second international joint conference on artificial intelligence, 2011
332011
Smartlocks: lock acquisition scheduling for self-aware synchronization
J Eastep, D Wingate, MD Santambrogio, A Agarwal
Proceedings of the 7th international conference on Autonomic computing, 215-224, 2010
332010
Smart data structures: an online machine learning approach to multicore data structures
J Eastep, D Wingate, A Agarwal
Proceedings of the 8th ACM international conference on Autonomic computing …, 2011
312011
On discovery and learning of models with predictive representations of state for agents with continuous actions and observations
D Wingate, S Singh
Proceedings of the 6th international joint conference on Autonomous agents …, 2007
292007
Kernel predictive linear Gaussian models for nonlinear stochastic dynamical systems
D Wingate, S Singh
Proceedings of the 23rd international Conference on Machine Learning, 1017-1024, 2006
292006
Predictive linear-Gaussian models of stochastic dynamical systems
M Rudary, S Singh, D Wingate
arXiv preprint arXiv:1207.1416, 2012
282012
Exponential Family Predictive Representations of State.
D Wingate
262008
P3VI: A partitioned, prioritized, parallel value iterator
D Wingate, KD Seppi
Proceedings of the twenty-first international conference on Machine learning …, 2004
262004
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Articles 1–20