Poupart, Pascal

104 publications

TMLR 2025 A Comprehensive Survey on Inverse Constrained Reinforcement Learning: Definitions, Progress and Challenges Guiliang Liu, Sheng Xu, Shicheng Liu, Ashish Gaurav, Sriram Ganapathi Subramanian, Pascal Poupart

AISTATS 2025 Learning to Negotiate via Voluntary Commitment Shuhui Zhu, Baoxiang Wang, Sriram Ganapathi Subramanian, Pascal Poupart

ICML 2025 Reflect-Then-Plan: Offline Model-Based Planning Through a Doubly Bayesian Lens Jihwan Jeong, Xiaoyu Wang, Jingmin Wang, Scott Sanner, Pascal Poupart

ICML 2025 Towards Cost-Effective Reward Guided Text Generation Ahmad Rashid, Ruotian Wu, Rongqi Fan, Hongliang Li, Agustinus Kristiadi, Pascal Poupart

ICLR 2025 Understanding Constraint Inference in Safety-Critical Inverse Reinforcement Learning Bo Yue, Shufan Wang, Ashish Gaurav, Jian Li, Pascal Poupart, Guiliang Liu

TMLR 2025 When Should Reinforcement Learning Use Causal Reasoning? Oliver Schulte, Pascal Poupart

ICMLW 2024 A Critical Look at Tokenwise Reward-Guided Text Generation Ahmad Rashid, Ruotian Wu, Julia Grosse, Agustinus Kristiadi, Pascal Poupart

ICML 2024 A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization over Molecules? Agustinus Kristiadi, Felix Strieth-Kalthoff, Marta Skreta, Pascal Poupart, Alan Aspuru-Guzik, Geoff Pleiss

AAAI 2024 Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space Mohsin Hasan, Guojun Zhang, Kaiyang Guo, Xi Chen, Pascal Poupart

ICML 2024 Confidence Aware Inverse Constrained Reinforcement Learning Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi, Kasra Rezaee, Pascal Poupart

JMLR 2024 Label Alignment Regularization for Distribution Shift Ehsan Imani, Guojun Zhang, Runjia Li, Jun Luo, Pascal Poupart, Philip H.S. Torr, Yangchen Pan

AISTATS 2024 Preventing Arbitrarily High Confidence on Far-Away Data in Point-Estimated Discriminative Neural Networks Ahmad Rashid, Serena Hacker, Guojun Zhang, Agustinus Kristiadi, Pascal Poupart

NeurIPS 2024 Subject-Driven Text-to-Image Generation via Preference-Based Reinforcement Learning Yanting Miao, William Loh, Suraj Kothawade, Pascal Poupart, Abdullah Rashwan, Yeqing Li

NeurIPS 2023 An Alternative to Variance: Gini Deviation for Risk-Averse Policy Gradient Yudong Luo, Guiliang Liu, Pascal Poupart, Yangchen Pan

NeurIPS 2023 BatchNorm Allows Unsupervised Radial Attacks Amur Ghose, Apurv Gupta, Yaoliang Yu, Pascal Poupart

ICLR 2023 Benchmarking Constraint Inference in Inverse Reinforcement Learning Guiliang Liu, Yudong Luo, Ashish Gaurav, Kasra Rezaee, Pascal Poupart

ICLR 2023 Learning Soft Constraints from Constrained Expert Demonstrations Ashish Gaurav, Kasra Rezaee, Guiliang Liu, Pascal Poupart

NeurIPS 2023 Multi-Modal Inverse Constrained Reinforcement Learning from a Mixture of Demonstrations Guanren Qiao, Guiliang Liu, Pascal Poupart, Zhiqiang Xu

AISTATS 2023 NTS-NOTEARS: Learning Nonparametric DBNs with Prior Knowledge Xiangyu Sun, Oliver Schulte, Guiliang Liu, Pascal Poupart

AAAI 2022 Decentralized Mean Field Games Sriram Ganapathi Subramanian, Matthew E. Taylor, Mark Crowley, Pascal Poupart

ICLR 2022 Distributional Reinforcement Learning with Monotonic Splines Yudong Luo, Guiliang Liu, Haonan Duan, Oliver Schulte, Pascal Poupart

NeurIPSW 2022 Geometric Attacks on Batch Normalization Amur Ghose, Apurv Gupta, Yaoliang Yu, Pascal Poupart

UAI 2022 Learning Functions on Multiple Sets Using Multi-Set Transformers Kira A. Selby, Ahmad Rashid, Ivan Kobyzev, Mehdi Rezagholizadeh, Pascal Poupart

ICLR 2022 Learning Object-Oriented Dynamics for Planning from Text Guiliang Liu, Ashutosh Adhikari, Amir-massoud Farahmand, Pascal Poupart

UAI 2022 Linearizing Contextual Bandits with Latent State Dynamics Elliot Nelson, Debarun Bhattacharjya, Tian Gao, Miao Liu, Djallel Bouneffouf, Pascal Poupart

JMLR 2022 Optimality and Stability in Non-Convex Smooth Games Guojun Zhang, Pascal Poupart, Yaoliang Yu

NeurIPS 2022 Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game Guiliang Liu, Yudong Luo, Oliver Schulte, Pascal Poupart

NeurIPS 2021 Learning Tree Interpretation from Object Representation for Deep Reinforcement Learning Guiliang Liu, Xiangyu Sun, Oliver Schulte, Pascal Poupart

ICCV 2021 Prediction by Anticipation: An Action-Conditional Prediction Method Based on Interaction Learning Ershad Banijamali, Mohsen Rohani, Elmira Amirloo, Jun Luo, Pascal Poupart

NeurIPS 2021 Quantifying and Improving Transferability in Domain Generalization Guojun Zhang, Han Zhao, Yaoliang Yu, Pascal Poupart

CVPR 2021 Self-Supervised Simultaneous Multi-Step Prediction of Road Dynamics and Cost mAP Elmira Amirloo, Mohsen Rohani, Ershad Banijamali, Jun Luo, Pascal Poupart

UAI 2020 Batch Norm with Entropic Regularization Turns Deterministic Autoencoders into Generative Models Amur Ghose, Abdullah Rashwan, Pascal Poupart

AAAI 2020 Diachronic Embedding for Temporal Knowledge Graph Completion Rishab Goel, Seyed Mehran Kazemi, Marcus A. Brubaker, Pascal Poupart

IJCAI 2020 Inverse Reinforcement Learning for Team Sports: Valuing Actions and Players Yudong Luo, Oliver Schulte, Pascal Poupart

NeurIPS 2020 Learning Agent Representations for Ice Hockey Guiliang Liu, Oliver Schulte, Pascal Poupart, Mike Rudd, Mehrsan Javan

NeurIPS 2020 Learning Dynamic Belief Graphs to Generalize on Text-Based Games Ashutosh Adhikari, Xingdi Yuan, Marc-Alexandre Côté, Mikuláš Zelinka, Marc-Antoine Rondeau, Romain Laroche, Pascal Poupart, Jian Tang, Adam Trischler, Will Hamilton

ICML 2020 Online Bayesian Moment Matching Based SAT Solver Heuristics Haonan Duan, Saeed Nejati, George Trimponias, Pascal Poupart, Vijay Ganesh

ICLR 2020 Progressive Memory Banks for Incremental Domain Adaptation Nabiha Asghar, Lili Mou, Kira A. Selby, Kevin D. Pantasdo, Pascal Poupart, Xin Jiang

JMLR 2020 Representation Learning for Dynamic Graphs: A Survey Seyed Mehran Kazemi, Rishab Goel, Kshitij Jain, Ivan Kobyzev, Akshay Sethi, Peter Forsyth, Pascal Poupart

IJCAI 2020 Unsupervised Multilingual Alignment Using Wasserstein Barycenter Xin Lian, Kshitij Jain, Jakub Truszkowski, Pascal Poupart, Yaoliang Yu

UAI 2019 Comparing EM with GD in Mixture Models of Two Components Guojun Zhang, Pascal Poupart, George Trimponias

ICCVW 2019 Matrix Nets: A New Deep Architecture for Object Detection Abdullah Rashwan, Agastya Kalra, Pascal Poupart

UAI 2019 On the Relationship Between Satisfiability and Markov Decision Processes Ricardo Salmon, Pascal Poupart

ICMLW 2019 Progressive Memory Banks for Incremental Domain Adaptation Nabiha Asghar, Lili Mou, Kira A. Selby, Kevin D. Pantasdo, Pascal Poupart, Xin Jiang

IJCAI 2018 An Empirical Study of Branching Heuristics Through the Lens of Global Learning Rate Jia Liang, Hari Govind V. K., Pascal Poupart, Krzysztof Czarnecki, Vijay Ganesh

PGM 2018 An Empirical Study of Methods for SPN Learning and Inference Cory J. Butz, Jhonatan S. Oliveira, André E. Santos, André L. Teixeira, Pascal Poupart, Agastya Kalra

NeurIPS 2018 Deep Homogeneous Mixture Models: Representation, Separation, and Approximation Priyank Jaini, Pascal Poupart, Yaoliang Yu

PGM 2018 Discriminative Training of Sum-Product Networks by Extended Baum-Welch Abdullah Rashwan, Pascal Poupart, Chen Zhitang

NeurIPS 2018 Monte-Carlo Tree Search for Constrained POMDPs Jongmin Lee, Geon-hyeong Kim, Pascal Poupart, Kee-Eung Kim

NeurIPS 2018 Online Structure Learning for Feed-Forward and Recurrent Sum-Product Networks Agastya Kalra, Abdullah Rashwan, Wei-Shou Hsu, Pascal Poupart, Prashant Doshi, Georgios Trimponias

AAAI 2018 Order-Planning Neural Text Generation from Structured Data Lei Sha, Lili Mou, Tianyu Liu, Pascal Poupart, Sujian Li, Baobao Chang, Zhifang Sui

PGM 2018 Prometheus : Directly Learning Acyclic Directed Graph Structures for Sum-Product Networks Priyank Jaini, Amur Ghose, Pascal Poupart

NeurIPS 2018 Unsupervised Video Object Segmentation for Deep Reinforcement Learning Vikash Goel, Jameson Weng, Pascal Poupart

IJCAI 2017 Constrained Bayesian Reinforcement Learning via Approximate Linear Programming Jongmin Lee, Youngsoo Jang, Pascal Poupart, Kee-Eung Kim

AAAI 2017 Discovering Conversational Dependencies Between Messages in Dialogs Wenchao Du, Pascal Poupart, Wei Xu

ICLR 2017 Online Bayesian Transfer Learning for Sequential Data Modeling Priyank Jaini, Zhitang Chen, Pablo Carbajal, Edith Law, Laura Middleton, Kayla Regan, Mike Schaekermann, George Trimponias, James Tung, Pascal Poupart

ICLR 2017 Online Structure Learning for Sum-Product Networks with Gaussian Leaves Wilson Hsu, Agastya Kalra, Pascal Poupart

NeurIPS 2016 A Unified Approach for Learning the Parameters of Sum-Product Networks Han Zhao, Pascal Poupart, Geoffrey J. Gordon

AAAI 2016 Decision Sum-Product-Max Networks Mazen Melibari, Pascal Poupart, Prashant Doshi

PGM 2016 Dynamic Sum Product Networks for Tractable Inference on Sequence Data Mazen Melibari, Pascal Poupart, Prashant Doshi, George Trimponias

AAAI 2016 Exponential Recency Weighted Average Branching Heuristic for SAT Solvers Jia Hui Liang, Vijay Ganesh, Pascal Poupart, Krzysztof Czarnecki

PGM 2016 Online Algorithms for Sum-Product Networks with Continuous Variables Priyank Jaini, Abdullah Rashwan, Han Zhao, Yue Liu, Ershad Banijamali, Zhitang Chen, Pascal Poupart

NeurIPS 2016 Online Bayesian Moment Matching for Topic Modeling with Unknown Number of Topics Wei-Shou Hsu, Pascal Poupart

AISTATS 2016 Online Relative Entropy Policy Search Using Reproducing Kernel Hilbert Space Embeddings Zhitang Chen, Pascal Poupart, Yanhui Geng

AISTATS 2016 Online and Distributed Bayesian Moment Matching for Parameter Learning in Sum-Product Networks Abdullah Rashwan, Han Zhao, Pascal Poupart

IJCAI 2016 Sum-Product-Max Networks for Tractable Decision Making Mazen Melibari, Pascal Poupart, Prashant Doshi

AAAI 2015 Approximate Linear Programming for Constrained Partially Observable Markov Decision Processes Pascal Poupart, Aarti Malhotra, Pei Pei, Kee-Eung Kim, Bongseok Goh, Michael Bowling

ICML 2015 On the Relationship Between Sum-Product Networks and Bayesian Networks Han Zhao, Mazen Melibari, Pascal Poupart

IJCAI 2015 Self-Adaptive Hierarchical Sentence Model Han Zhao, Zhengdong Lu, Pascal Poupart

AAAI 2015 SoF: Soft-Cluster Matrix Factorization for Probabilistic Clustering Han Zhao, Pascal Poupart, Yongfeng Zhang, Martin Lysy

AAAI 2014 A Novel Single-DBN Generative Model for Optimizing POMDP Controllers by Probabilistic Inference Igor Kiselev, Pascal Poupart

IJCAI 2013 Isomorph-Free Branch and Bound Search for Finite State Controllers Marek Grzes, Pascal Poupart, Jesse Hoey

ECML-PKDD 2013 Iterative Model Refinement of Recommender MDPs Based on Expert Feedback Omar Zia Khan, Pascal Poupart, John Mark Agosta

IJCAI 2013 Learning Community-Based Preferences via Dirichlet Process Mixtures of Gaussian Processes Ehsan Abbasnejad, Scott Sanner, Edwin V. Bonilla, Pascal Poupart

NeurIPS 2012 Cost-Sensitive Exploration in Bayesian Reinforcement Learning Dongho Kim, Kee-eung Kim, Pascal Poupart

AAAI 2012 Hierarchical Double Dirichlet Process Mixture of Gaussian Processes Aditya Tayal, Pascal Poupart, Yuying Li

NeurIPS 2012 Symbolic Dynamic Programming for Continuous State and Observation POMDPs Zahra Zamani, Scott Sanner, Pascal Poupart, Kristian Kersting

CVPRW 2011 3D Pose Tracking of Walker Users' Lower Limb with a Structured-Light Camera on a Moving Platform Richard Zhi-Ling Hu, Adam Hartfiel, James Yungjen Tung, Adel H. Fakih, Jesse Hoey, Pascal Poupart

ECML-PKDD 2011 Analyzing and Escaping Local Optima in Planning as Inference for Partially Observable Domains Pascal Poupart, Tobias Lang, Marc Toussaint

AISTATS 2011 Asymptotic Theory for Linear-Chain Conditional Random Fields Mathieu Sinn, Pascal Poupart

NeurIPS 2011 Automated Refinement of Bayes Networks' Parameters Based on Test Ordering Constraints Omar Z. Khan, Pascal Poupart, John-mark M. Agosta

IJCAI 2011 Continuous Correlated Beta Processes Robby Goetschalckx, Pascal Poupart, Jesse Hoey

JAIR 2011 Exploiting Structure in Weighted Model Counting Approaches to Probabilistic Inference Wei Li, Pascal Poupart, Peter van Beek

IJCAI 2011 Point-Based Value Iteration for Constrained POMDPs Dongho Kim, Jaesong Lee, Kee-Eung Kim, Pascal Poupart

UAI 2010 Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker Farheen Omar, Mathieu Sinn, Jakub Truszkowski, Pascal Poupart, James Yungjen Tung, Allen Caine

AAAI 2008 Exploiting Causal Independence Using Weighted Model Counting Wei Li, Pascal Poupart, Peter van Beek

UAI 2008 Hierarchical POMDP Controller Optimization by Likelihood Maximization Marc Toussaint, Laurent Charlin, Pascal Poupart

ICML 2006 An Analytic Solution to Discrete Bayesian Reinforcement Learning Pascal Poupart, Nikos Vlassis, Jesse Hoey, Kevin Regan

NeurIPS 2006 Automated Hierarchy Discovery for Planning in Partially Observable Environments Laurent Charlin, Pascal Poupart, Romy Shioda

AAAI 2006 Bayesian Reputation Modeling in E-Marketplaces Sensitive to Subjectivity, Deception and Change Kevin Regan, Pascal Poupart, Robin Cohen

AAAI 2006 Compact, Convex Upper Bound Iteration for Approximate POMDP Planning Tao Wang, Pascal Poupart, Michael H. Bowling, Dale Schuurmans

AAAI 2006 Performing Incremental Bayesian Inference by Dynamic Model Counting Wei Li, Peter van Beek, Pascal Poupart

JMLR 2006 Point-Based Value Iteration for Continuous POMDPs Josep M. Porta, Nikos Vlassis, Matthijs T.J. Spaan, Pascal Poupart

IJCAI 2005 A Decision-Theoretic Approach to Task Assistance for Persons with Dementia Jennifer Boger, Pascal Poupart, Jesse Hoey, Craig Boutilier, Geoff R. Fernie, Alex Mihailidis

IJCAI 2005 Regret-Based Utility Elicitation in Constraint-Based Decision Problems Craig Boutilier, Relu Patrascu, Pascal Poupart, Dale Schuurmans

IJCAI 2005 Solving POMDPs with Continuous or Large Discrete Observation Spaces Jesse Hoey, Pascal Poupart

NeurIPS 2004 VDCBPI: An Approximate Scalable Algorithm for Large POMDPs Pascal Poupart, Craig Boutilier

NeurIPS 2003 Bounded Finite State Controllers Pascal Poupart, Craig Boutilier

AAAI 2002 Greedy Linear Value-Approximation for Factored Markov Decision Processes Relu Patrascu, Pascal Poupart, Dale Schuurmans, Craig Boutilier, Carlos Guestrin

AAAI 2002 Piecewise Linear Value Function Approximation for Factored MDPs Pascal Poupart, Craig Boutilier, Relu Patrascu, Dale Schuurmans

NeurIPS 2002 Value-Directed Compression of POMDPs Pascal Poupart, Craig Boutilier

UAI 2001 Value-Directed Sampling Methods for POMDPs Pascal Poupart, Luis E. Ortiz, Craig Boutilier

UAI 2001 Vector-Space Analysis of Belief-State Approximation for POMDPs Pascal Poupart, Craig Boutilier

UAI 2000 Value-Directed Belief State Approximation for POMDPs Pascal Poupart, Craig Boutilier