David Wingate
Lightweight implementations of probabilistic programming languages via transformational compilation
D Wingate, A Stuhlmüller, N Goodman
Proceedings of the Fourteenth International Conference on Artificial …, 2011
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
Automated variational inference in probabilistic programming
D Wingate, T Weber
arXiv preprint arXiv:1301.1299, 2013
Prioritization Methods for Accelerating MDP Solvers.
D Wingate, KD Seppi, S Mahadevan
Journal of Machine Learning Research 6 (5), 2005
Acoustic source tracking and selection
D Wingate, ND Stein, B Vigoda, P Ohiomoba, B Donnelly
US Patent App. 14/847,818, 2016
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
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
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
Nonparametric Bayesian policy priors for reinforcement learning
F Doshi-Velez, D Wingate, N Roy, J Tenenbaum
Neural Information Processing Systems Foundation, 2010
Infinite dynamic Bayesian networks
F Doshi, D Wingate, JB Tenenbaum, N Roy
ICML, 2011
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
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
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
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
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
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
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
Predictive linear-Gaussian models of stochastic dynamical systems
M Rudary, S Singh, D Wingate
arXiv preprint arXiv:1207.1416, 2012
Apparatus, systems, and methods for providing intelligent vehicular systems and services
D Wingate, H Weinberg, B Vigoda
US Patent App. 15/121,435, 2016
Exponential Family Predictive Representations of State.
D Wingate
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학술자료 1–20