Representation learning for dynamic graphs: A survey SM Kazemi, R Goel, K Jain, I Kobyzev, A Sethi, P Forsyth, P Poupart Journal of Machine Learning Research 21 (70), 1-73, 2020 | 485 | 2020 |
Time2vec: Learning a vector representation of time SM Kazemi, R Goel, S Eghbali, J Ramanan, J Sahota, S Thakur, S Wu, ... arXiv preprint arXiv:1907.05321, 2019 | 399 | 2019 |
An analytic solution to discrete Bayesian reinforcement learning P Poupart, N Vlassis, J Hoey, K Regan Proceedings of the 23rd international conference on Machine learning, 697-704, 2006 | 398 | 2006 |
Diachronic embedding for temporal knowledge graph completion R Goel, SM Kazemi, M Brubaker, P Poupart Proceedings of the AAAI conference on artificial intelligence 34 (04), 3988-3995, 2020 | 373 | 2020 |
Exploiting structure to efficiently solve large scale partially observable Markov decision processes P Poupart University of Toronto, 2005 | 345 | 2005 |
Point-based value iteration for continuous POMDPs JM Porta, N Vlassis, MTJ Spaan, P Poupart Massachusetts Institute of Technology, 2006 | 331 | 2006 |
Automated handwashing assistance for persons with dementia using video and a partially observable Markov decision process J Hoey, P Poupart, A von Bertoldi, T Craig, C Boutilier, A Mihailidis Computer Vision and Image Understanding 114 (5), 503-519, 2010 | 330 | 2010 |
Learning rate based branching heuristic for SAT solvers JH Liang, V Ganesh, P Poupart, K Czarnecki Theory and Applications of Satisfiability Testing–SAT 2016: 19th …, 2016 | 270 | 2016 |
Bounded finite state controllers P Poupart, C Boutilier Advances in neural information processing systems 16, 2003 | 265 | 2003 |
Self-adaptive hierarchical sentence model H Zhao, Z Lu, P Poupart arXiv preprint arXiv:1504.05070, 2015 | 258 | 2015 |
A decision-theoretic approach to task assistance for persons with dementia J Boger, P Poupart, J Hoey, C Boutilier, G Fernie, A Mihailidis Ijcai, 1293-1299, 2005 | 244 | 2005 |
A planning system based on Markov decision processes to guide people with dementia through activities of daily living J Boger, J Hoey, P Poupart, C Boutilier, G Fernie, A Mihailidis IEEE Transactions on Information Technology in Biomedicine 10 (2), 323-333, 2006 | 237 | 2006 |
Constraint-based optimization and utility elicitation using the minimax decision criterion C Boutilier, R Patrascu, P Poupart, D Schuurmans Artificial Intelligence 170 (8-9), 686-713, 2006 | 217 | 2006 |
Assisting persons with dementia during handwashing using a partially observable Markov decision process. J Hoey, A Von Bertoldi, P Poupart, A Mihailidis International Conference on Computer Vision Systems: Proceedings, 2007 | 195 | 2007 |
Affective neural response generation N Asghar, P Poupart, J Hoey, X Jiang, L Mou Advances in Information Retrieval: 40th European Conference on IR Research …, 2018 | 191 | 2018 |
Factored partially observable Markov decision processes for dialogue management JD Williams, P Poupart, S Young Proc. IJCAI Workshop on Knowledge and Reasoning in Practical Dialogue …, 2005 | 172 | 2005 |
Value-directed compression of POMDPs P Poupart, C Boutilier Advances in neural information processing systems 15, 2002 | 171 | 2002 |
Bayesian reputation modeling in e-marketplaces sensitive to subjectivity, deception and change K Regan, P Poupart, R Cohen Proceedings of the national conference on artificial intelligence 21 (2), 1206, 2006 | 168 | 2006 |
On improving deep reinforcement learning for pomdps P Zhu, X Li, P Poupart, G Miao arXiv preprint arXiv:1704.07978, 2017 | 164 | 2017 |
Solving POMDPs with continuous or large discrete observation spaces J Hoey, P Poupart IJCAI, 1332-1338, 2005 | 163 | 2005 |