Yitao Liang
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A semantic loss function for deep learning with symbolic knowledge
J Xu, Z Zhang, T Friedman, Y Liang, GV Broeck
Proceedings of the 35th International Conference on Machine Learning (ICML), 2018
State of the art control of atari games using shallow reinforcement learning
Y Liang, MC Machado, E Talvitie, M Bowling
Proceedings of the 15th International Conference on Autonomous Agents …, 2016
Horizon: Facebook's open source applied reinforcement learning platform
J Gauci, E Conti, Y Liang, K Virochsiri, Y He, Z Kaden, V Narayanan, X Ye, ...
arXiv preprint arXiv:1811.00260, 2018
Learning the structure of probabilistic sentential decision diagrams
Y Liang, J Bekker, G Van den Broeck
Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence …, 2017
Learning Logistic Circuits
Y Liang, G Van den Broeck
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence …, 2019
What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features
P Khosravi, Y Liang, YJ Choi, GV Broeck
Proceedings of the 26th International Joint Conference on Artificial …, 2019
On Tractable Computation of Expected Predictions
P Khosravi, YJ Choi, Y Liang, A Vergari, GV Broeck
Advances in Neural Information Processing Systems 32 (NeurIPS 2019), 2019
Handling missing data in decision trees: A probabilistic approach
P Khosravi, A Vergari, YJ Choi, Y Liang, GV Broeck
arXiv preprint arXiv:2006.16341, 2020
SAM: Squeeze-and-Mimic Networks for Conditional Visual Driving Policy Learning
A Zhao, T He, Y Liang, H Huang, G Van den Broeck, S Soatto
Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing
Z Hu, Y Liang, J Zhang, Z Li, Y Liu
Advances in Neural Information Processing Systems 31 (NeurIPS 2018), 2018
Towards compact interpretable models: shrinking of learned probabilistic sentential decision diagrams
Y Liang, G Van den Broeck
IJCAI-17 Workshop on Explainable AI (XAI), 31, 2017
Juice: A julia package for logic and probabilistic circuits
M Dang, P Khosravi, Y Liang, A Vergari, G Van den Broeck
Proceedings of the AAAI Conference on Artificial Intelligence 35 (18), 16020 …, 2021
Semantic and generalized entropy loss functions for semi-supervised deep learning
K Gajowniczek, Y Liang, T Friedman, T Ząbkowski, G Van den Broeck
Entropy 22 (3), 334, 2020
On effective parallelization of monte carlo tree search
A Liu, Y Liang, J Liu, GV Broeck, J Chen
arXiv preprint arXiv:2006.08785, 2020
Off-Policy Deep Reinforcement Learning with Analogous Disentangled Exploration
A Liu, Y Liang, G Van den Broeck
Proceedings of the 19th International Conference on Autonomous Agents and …, 2020
IL-Strudel: independence-based learning of structured-decomposable probabilistic circuit ensembles
S Kowshik, Y Liang, G Van den Broeck
The 4th Workshop on Tractable Probabilistic Modeling, 2021
Towards an Interpretable Latent Space in Structured Models for Video Prediction
R Gupta, V Sharma, Y Jain, Y Liang, GV Broeck, P Singla
arXiv preprint arXiv:2107.07713, 2021
Unifying Probabilistic Reasoning, Learning, and Classification with Circuit Representations
Y Liang
University of California, Los Angeles, 2021
Unified Representations for Learning and Reasoning
Y Liang
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