| 2025 | AISTATS | Learning to Negotiate via Voluntary Commitment. | Shuhui Zhu, Baoxiang Wang, Sriram Ganapathi Subramanian, Pascal Poupart |
| 2025 | ICCV | Target Attribute Diffusion Models. | William Loh, Yanting Miao, Pascal Poupart, Suraj Kothawade |
| 2025 | ICLR | Understanding Constraint Inference in Safety-Critical Inverse Reinforcement Learning. | Bo Yue, Shufan Wang, Ashish Gaurav, Jian Li, Pascal Poupart, Guiliang Liu |
| 2025 | ICML | Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens. | Jihwan Jeong, Xiaoyu Wang, Jingmin Wang, Scott Sanner, Pascal Poupart |
| 2025 | ICML | Towards Cost-Effective Reward Guided Text Generation. | Ahmad Rashid, Ruotian Wu, Rongqi Fan, Hongliang Li, Agustinus Kristiadi, Pascal Poupart |
| 2024 | AAAI | Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space. | Mohsin Hasan, Guojun Zhang, Kaiyang Guo, Xi Chen, Pascal Poupart |
| 2024 | AISTATS | Preventing Arbitrarily High Confidence on Far-Away Data in Point-Estimated Discriminative Neural Networks. | Ahmad Rashid, Serena Hacker, Guojun Zhang, Agustinus Kristiadi, Pascal Poupart |
| 2024 | ICML | 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, Aln Aspuru-Guzik, Geoff Pleiss |
| 2024 | ICML | Confidence Aware Inverse Constrained Reinforcement Learning. | Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi, Kasra Rezaee, Pascal Poupart |
| 2023 | ACL | Attribute Controlled Dialogue Prompting. | Runcheng Liu, Ahmad Rashid, Ivan Kobyzev, Mehdi Rezagholizadeh, Pascal Poupart |
| 2023 | AISTATS | NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge. | Xiangyu Sun, Oliver Schulte, Guiliang Liu, Pascal Poupart |
| 2023 | EACL | Do we need Label Regularization to Fine-tune Pre-trained Language Models? | Ivan Kobyzev, Aref Jafari, Mehdi Rezagholizadeh, Tianda Li, Alan Do-Omri, Peng Lu, Pascal Poupart, Ali Ghodsi |
| 2023 | EMNLP | Contrastive Deterministic Autoencoders For Language Modeling. | Amur Ghose, Pascal Poupart |
| 2023 | ICLR | Learning Soft Constraints From Constrained Expert Demonstrations. | Ashish Gaurav, Kasra Rezaee, Guiliang Liu, Pascal Poupart |
| 2023 | ICLR | Benchmarking Constraint Inference in Inverse Reinforcement Learning. | Guiliang Liu, Yudong Luo, Ashish Gaurav, Kasra Rezaee, Pascal Poupart |
| 2022 | AAAI | Decentralized Mean Field Games. | Sriram Ganapathi Subramanian, Matthew E. Taylor, Mark Crowley, Pascal Poupart |
| 2022 | ACL | WatClaimCheck: A new Dataset for Claim Entailment and Inference. | Kashif Khan, Ruizhe Wang, Pascal Poupart |
| 2022 | COLING | CILDA: Contrastive Data Augmentation Using Intermediate Layer Knowledge Distillation. | Md. Akmal Haidar, Mehdi Rezagholizadeh, Abbas Ghaddar, Khalil Bibi, Philippe Langlais, Pascal Poupart |
| 2022 | EMNLP | Continuation KD: Improved Knowledge Distillation through the Lens of Continuation Optimization. | Aref Jafari, Ivan Kobyzev, Mehdi Rezagholizadeh, Pascal Poupart, Ali Ghodsi |
| 2022 | ICLR | Learning Object-Oriented Dynamics for Planning from Text. | Guiliang Liu, Ashutosh Adhikari, Amir-massoud Farahmand, Pascal Poupart |
| 2022 | ICLR | Distributional Reinforcement Learning with Monotonic Splines. | Yudong Luo, Guiliang Liu, Haonan Duan, Oliver Schulte, Pascal Poupart |
| 2022 | NAACL | RAIL-KD: RAndom Intermediate Layer Mapping for Knowledge Distillation. | Md. Akmal Haidar, Nithin Anchuri, Mehdi Rezagholizadeh, Abbas Ghaddar, Philippe Langlais, Pascal Poupart |
| 2022 | UAI | Linearizing contextual bandits with latent state dynamics. | Elliot Nelson, Debarun Bhattacharjya, Tian Gao, Miao Liu, Djallel Bouneffouf, Pascal Poupart |
| 2022 | UAI | Learning functions on multiple sets using multi-set transformers. | Kira A. Selby, Ahmad Rashid, Ivan Kobyzev, Mehdi Rezagholizadeh, Pascal Poupart |
| 2021 | CVPR | Self-Supervised Simultaneous Multi-Step Prediction of Road Dynamics and Cost Map. | Elmira Amirloo Abolfathi, Mohsen Rohani, Ershad Banijamali, Jun Luo, Pascal Poupart |
| 2021 | ICCV | Prediction by Anticipation: An Action-Conditional Prediction Method based on Interaction Learning. | Ershad Banijamali, Mohsen Rohani, Elmira Amirloo Abolfathi, Jun Luo, Pascal Poupart |
| 2020 | AAAI | Diachronic Embedding for Temporal Knowledge Graph Completion. | Rishab Goel, Seyed Mehran Kazemi, Marcus A. Brubaker, Pascal Poupart |
| 2020 | ICLR | Progressive Memory Banks for Incremental Domain Adaptation. | Nabiha Asghar, Lili Mou, Kira A. Selby, Kevin D. Pantasdo, Pascal Poupart, Xin Jiang |
| 2020 | ICML | Online Bayesian Moment Matching based SAT Solver Heuristics. | Haonan Duan, Saeed Nejati, George Trimponias, Pascal Poupart, Vijay Ganesh |
| 2020 | IJCAI | Unsupervised Multilingual Alignment using Wasserstein Barycenter. | Xin Lian, Kshitij Jain, Jakub Truszkowski, Pascal Poupart, Yaoliang Yu |
| 2020 | IJCAI | Inverse Reinforcement Learning for Team Sports: Valuing Actions and Players. | Yudong Luo, Oliver Schulte, Pascal Poupart |
| 2020 | UAI | Batch norm with entropic regularization turns deterministic autoencoders into generative models. | Amur Ghose, Abdullah Rashwan, Pascal Poupart |
| 2019 | ICASSP | Why Do Neural Dialog Systems Generate Short and Meaningless Replies? a Comparison between Dialog and Translation. | Bolin Wei, Shuai Lu, Lili Mou, Hao Zhou, Pascal Poupart, Ge Li, Zhi Jin |
| 2019 | UAI | On the Relationship Between Satisfiability and Markov Decision Processes. | Ricardo Salmon, Pascal Poupart |
| 2019 | UAI | Comparing EM with GD in Mixture Models of Two Components. | Guojun Zhang, Pascal Poupart, George Trimponias |
| 2018 | AAAI | Order-Planning Neural Text Generation From Structured Data. | Lei Sha, Lili Mou, Tianyu Liu, Pascal Poupart, Sujian Li, Baobao Chang, Zhifang Sui |
| 2018 | COLING | Variational Attention for Sequence-to-Sequence Models. | Hareesh Bahuleyan, Lili Mou, Olga Vechtomova, Pascal Poupart |
| 2018 | ECIR | Affective Neural Response Generation. | Nabiha Asghar, Pascal Poupart, Jesse Hoey, Xin Jiang, Lili Mou |
| 2018 | IJCAI | 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 |
| 2017 | AAAI | Discovering Conversational Dependencies between Messages in Dialogs. | Wenchao Du, Pascal Poupart, Wei Xu |
| 2017 | ICLR | Online Structure Learning for Sum-Product Networks with Gaussian Leaves. | Wilson Hsu, Agastya Kalra, Pascal Poupart |
| 2017 | ICLR | 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 |
| 2017 | IJCAI | Constrained Bayesian Reinforcement Learning via Approximate Linear Programming. | Jongmin Lee, Youngsoo Jang, Pascal Poupart, Kee-Eung Kim |
| 2017 | IJCNN | Generative mixture of networks. | Ershad Banijamali, Ali Ghodsi, Pascal Poupart |
| 2017 | SAT | An Empirical Study of Branching Heuristics Through the Lens of Global Learning Rate. | Jia Hui Liang, Hari Govind V. K., Pascal Poupart, Krzysztof Czarnecki, Vijay Ganesh |
| 2017 | SAT | A Propagation Rate Based Splitting Heuristic for Divide-and-Conquer Solvers. | Saeed Nejati, Zack Newsham, Joseph Scott, Jia Hui Liang, Catherine H. Gebotys, Pascal Poupart, Vijay Ganesh |
| 2016 | AAAI | Exponential Recency Weighted Average Branching Heuristic for SAT Solvers. | Jia Hui Liang, Vijay Ganesh, Pascal Poupart, Krzysztof Czarnecki |
| 2016 | AAAI | Decision Sum-Product-Max Networks. | Mazen Melibari, Pascal Poupart, Prashant Doshi |
| 2016 | AISTATS | Online Relative Entropy Policy Search using Reproducing Kernel Hilbert Space Embeddings. | Zhitang Chen, Pascal Poupart, Yanhui Geng |
| 2016 | AISTATS | Online and Distributed Bayesian Moment Matching for Parameter Learning in Sum-Product Networks. | Abdullah Rashwan, Han Zhao, Pascal Poupart |
| 2016 | ICNP | Online flow size prediction for improved network routing. | Pascal Poupart, Zhitang Chen, Priyank Jaini, Fred Fung, Hengky Susanto, Yanhui Geng, Li Chen, Kai Chen, Hao Jin |
| 2016 | IJCAI | Sum-Product-Max Networks for Tractable Decision Making. | Mazen Melibari, Pascal Poupart, Prashant Doshi |
| 2016 | SAT | Learning Rate Based Branching Heuristic for SAT Solvers. | Jia Hui Liang, Vijay Ganesh, Pascal Poupart, Krzysztof Czarnecki |
| 2015 | AAAI | Approximate Linear Programming for Constrained Partially Observable Markov Decision Processes. | Pascal Poupart, Aarti Malhotra, Pei Pei, Kee-Eung Kim, Bongseok Goh, Michael Bowling |
| 2015 | AAAI | SoF: Soft-Cluster Matrix Factorization for Probabilistic Clustering. | Han Zhao, Pascal Poupart, Yongfeng Zhang, Martin Lysy |
| 2015 | ICML | On the Relationship between Sum-Product Networks and Bayesian Networks. | Han Zhao, Mazen Melibari, Pascal Poupart |
| 2015 | IJCAI | Self-Adaptive Hierarchical Sentence Model. | Han Zhao, Zhengdong Lu, Pascal Poupart |
| 2014 | AAAI | A Novel Single-DBN Generative Model for Optimizing POMDP Controllers by Probabilistic Inference. | Igor Kiselev, Pascal Poupart |
| 2013 | IJCAI | Learning Community-Based Preferences via Dirichlet Process Mixtures of Gaussian Processes. | Ehsan Abbasnejad, Scott Sanner, Edwin V. Bonilla, Pascal Poupart |
| 2013 | IJCAI | Isomorph-Free Branch and Bound Search for Finite State Controllers. | Marek Grzes, Pascal Poupart, Jesse Hoey |
| 2012 | AAAI | Hierarchical Double Dirichlet Process Mixture of Gaussian Processes. | Aditya Tayal, Pascal Poupart, Yuying Li |
| 2012 | ICMLA | Muscle Categorization Using Quantitative Needle Electromyography: A 2-Stage Gaussian Mixture Model Based Approach. | Meena Abdelmaseeh, Pascal Poupart, Benn Smith, Daniel W. Stashuk |
| 2011 | CVPR | 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 |
| 2011 | ICMLA | Error Bounds for Online Predictions of Linear-Chain Conditional Random Fields: Application to Activity Recognition for Users of Rolling Walkers. | Mathieu Sinn, Pascal Poupart |
| 2011 | IJCAI | Continuous Correlated Beta Processes. | Robby Goetschalckx, Pascal Poupart, Jesse Hoey |
| 2011 | IJCAI | Point-Based Value Iteration for Constrained POMDPs. | Dongho Kim, Jaesong Lee, Kee-Eung Kim, Pascal Poupart |
| 2010 | UAI | 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 |
| 2008 | AAAI | Exploiting Causal Independence Using Weighted Model Counting. | Wei Li, Pascal Poupart, Peter van Beek |
| 2008 | ISAIM | Model-based Bayesian Reinforcement Learning in Partially Observable Domains. | Pascal Poupart, Nikos Vlassis |
| 2008 | UAI | Hierarchical POMDP Controller Optimization by Likelihood Maximization. | Marc Toussaint, Laurent Charlin, Pascal Poupart |
| 2008 | UIST | Is the sky pure today? AwkChecker: an assistive tool for detecting and correcting collocation errors. | Taehyun Park, Edward Lank, Pascal Poupart, Michael A. Terry |
| 2007 | EMNLP | Generating Lexical Analogies Using Dependency Relations. | Andy Chiu, Pascal Poupart, Chrysanne DiMarco |
| 2006 | AAAI | Performing Incremental Bayesian Inference by Dynamic Model Counting. | Wei Li, Peter van Beek, Pascal Poupart |
| 2006 | AAAI | Bayesian Reputation Modeling in E-Marketplaces Sensitive to Subjectivity, Deception and Change. | Kevin Regan, Pascal Poupart, Robin Cohen |
| 2006 | AAAI | Compact, Convex Upper Bound Iteration for Approximate POMDP Planning. | Tao Wang, Pascal Poupart, Michael H. Bowling, Dale Schuurmans |
| 2006 | ICML | An analytic solution to discrete Bayesian reinforcement learning. | Pascal Poupart, Nikos Vlassis, Jesse Hoey, Kevin Regan |
| 2005 | IJCAI | A Decision-Theoretic Approach to Task Assistance for Persons with Dementia. | Jennifer Boger, Pascal Poupart, Jesse Hoey, Craig Boutilier, Geoff R. Fernie, Alex Mihailidis |
| 2005 | IJCAI | Regret-based Utility Elicitation in Constraint-based Decision Problems. | Craig Boutilier, Relu Patrascu, Pascal Poupart, Dale Schuurmans |
| 2005 | IJCAI | Solving POMDPs with Continuous or Large Discrete Observation Spaces. | Jesse Hoey, Pascal Poupart |
| 2005 | PST | The Advisor-POMDP: A Principled Approach to Trust through Reputation in Electronic Markets. | Kevin Regan, Robin Cohen, Pascal Poupart |
| 2005 | SIGdial | Partially Observable Markov Decision Processes with Continuous Observations for Dialogue Management. | Jason D. Williams, Pascal Poupart, Steve J. Young |
| 2003 | CP | Constraint-Based Optimization with the Minimax Decision Criterion. | Craig Boutilier, Relu Patrascu, Pascal Poupart, Dale Schuurmans |
| 2002 | AAAI | Greedy Linear Value-Approximation for Factored Markov Decision Processes. | Relu Patrascu, Pascal Poupart, Dale Schuurmans, Craig Boutilier, Carlos Guestrin |
| 2002 | AAAI | Piecewise Linear Value Function Approximation for Factored MDPs. | Pascal Poupart, Craig Boutilier, Relu Patrascu, Dale Schuurmans |
| 2001 | UAI | Vector-space Analysis of Belief-state Approximation for POMDPs. | Pascal Poupart, Craig Boutilier |
| 2001 | UAI | Value-Directed Sampling Methods for POMDPs. | Pascal Poupart, Luis E. Ortiz, Craig Boutilier |
| 2000 | UAI | Value-Directed Belief State Approximation for POMDPs. | Pascal Poupart, Craig Boutilier |