← Authors

Pascal Poupart

76 papers · 2006–2025 · 18 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (18) πŸ—ΊοΈ Taxonomy Completionist (27) πŸƒ Academic Marathon (19) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (10) 🌈 Renaissance Researcher (8) πŸŒ‰ Interdisciplinary Bridge 🌟 Keyword Trendsetter Combo (7) πŸ† Keyword Champion πŸ‘‘ Triple Crown 🌱 Topic Pioneer 🧬 Topic Evolution 🀝 Dynamic Duo (12) πŸ† Grand Slam πŸ”¬ Deep Specialist (12) ❓ The Questioner (2) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (11) ⚑ Prolific Year (9) πŸ—ƒοΈ Keyword Collector (85) πŸ’Ž Century Club (76)

Conferences

NIPS (19) IJCAI (8) AISTATS (6) ICML (6) ICLR (6) UAI (5) PGM (5) EMNLP (4) JMLR (4) AAAI (3) COLING (2) ACL (2) ICCV (1) EACL (1) CVPR (1) CONLL (1) NAACL (1) SEMEVAL (1)

Top co-authors

Guiliang Liu (12) Mehdi Rezagholizadeh (6) Han Zhao (6) Guojun Zhang (6) Oliver Schulte (6) Abdullah Rashwan (6) Ivan Kobyzev (5) Yaoliang Yu (5) Yudong Luo (5) Amur Ghose (4)

Keywords

sum-product network (10) knowledge distillation (4) representation learning (4) generative model (4) online learning (4) partially observable markov decision process (4) structure learning (4) contrastive learning (3) expectation maximization (3) bayesian moment matching (3) graphical model (3) parameter learning (3) bayesian inference (3) policy optimization (3) reinforcement learning (3) continuous state space (3) probabilistic graphical model (3) probabilistic modeling (2) unsupervised learning (2) non-convex optimization (2)

Papers

Towards Cost-Effective Reward Guided Text Generation ICML 2025
Time Is Effort: Estimating Human Post-Editing Time for Grammar Error Correction Tool Evaluation EMNLP 2025
Learning to Negotiate via Voluntary Commitment AISTATS 2025
Understanding Constraint Inference in Safety-Critical Inverse Reinforcement Learning ICLR 2025
Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens ICML 2025
Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space AAAI 2024
A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules? ICML 2024
Subject-driven Text-to-Image Generation via Preference-based Reinforcement Learning NIPS 2024
Preventing Arbitrarily High Confidence on Far-Away Data in Point-Estimated Discriminative Neural Networks AISTATS 2024
Confidence Aware Inverse Constrained Reinforcement Learning ICML 2024
Label Alignment Regularization for Distribution Shift JMLR 2024
Do we need Label Regularization to Fine-tune Pre-trained Language Models? EACL 2023
Contrastive Deterministic Autoencoders For Language Modeling EMNLP 2023
Benchmarking Constraint Inference in Inverse Reinforcement Learning ICLR 2023
Batchnorm Allows Unsupervised Radial Attacks NIPS 2023
Multi-Modal Inverse Constrained Reinforcement Learning from a Mixture of Demonstrations NIPS 2023
An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient NIPS 2023
Attribute Controlled Dialogue Prompting ACL 2023
NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge AISTATS 2023
Learning Soft Constraints From Constrained Expert Demonstrations ICLR 2023
Linearizing contextual bandits with latent state dynamics UAI 2022
CILDA: Contrastive Data Augmentation Using Intermediate Layer Knowledge Distillation COLING 2022
Learning functions on multiple sets using multi-set transformers UAI 2022
Decentralized Mean Field Games AAAI 2022
RAIL-KD: RAndom Intermediate Layer Mapping for Knowledge Distillation NAACL 2022
Distributional Reinforcement Learning with Monotonic Splines ICLR 2022
Optimality and Stability in Non-Convex Smooth Games JMLR 2022
Learning Object-Oriented Dynamics for Planning from Text ICLR 2022
WatClaimCheck: A new Dataset for Claim Entailment and Inference ACL 2022
Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game NIPS 2022
Continuation KD: Improved Knowledge Distillation through the Lens of Continuation Optimization EMNLP 2022
Quantifying and Improving Transferability in Domain Generalization NIPS 2021
Self-Supervised Simultaneous Multi-Step Prediction of Road Dynamics and Cost Map CVPR 2021
Prediction by Anticipation: An Action-Conditional Prediction Method Based on Interaction Learning ICCV 2021
Learning Tree Interpretation from Object Representation for Deep Reinforcement Learning NIPS 2021
Progressive Memory Banks for Incremental Domain Adaptation ICLR 2020
Online Bayesian Moment Matching based SAT Solver Heuristics ICML 2020
Batch norm with entropic regularization turns deterministic autoencoders into generative models UAI 2020
Learning Dynamic Belief Graphs to Generalize on Text-Based Games NIPS 2020
Learning Agent Representations for Ice Hockey NIPS 2020
Diachronic Embedding for Temporal Knowledge Graph Completion AAAI 2020
Representation Learning for Dynamic Graphs: A Survey JMLR 2020
Unsupervised Multilingual Alignment using Wasserstein Barycenter IJCAI 2020
Inverse Reinforcement Learning for Team Sports: Valuing Actions and Players IJCAI 2020
Comparing EM with GD in Mixture Models of Two Components UAI 2019
On the Relationship Between Satisfiability and Markov Decision Processes UAI 2019
An Empirical Study of Branching Heuristics through the Lens of Global Learning Rate IJCAI 2018
Monte-Carlo Tree Search for Constrained POMDPs NIPS 2018
Online Structure Learning for Feed-Forward and Recurrent Sum-Product Networks NIPS 2018
Unsupervised Video Object Segmentation for Deep Reinforcement Learning NIPS 2018
Deep Homogeneous Mixture Models: Representation, Separation, and Approximation NIPS 2018
Variational Attention for Sequence-to-Sequence Models COLING 2018
An Empirical Study of Methods for SPN Learning and Inference PGM 2018
Prometheus : Directly Learning Acyclic Directed Graph Structures for Sum-Product Networks PGM 2018
Discriminative Training of Sum-Product Networks by Extended Baum-Welch PGM 2018
Constrained Bayesian Reinforcement Learning via Approximate Linear Programming IJCAI 2017
Sum-Product-Max Networks for Tractable Decision Making IJCAI 2016
Online and Distributed Bayesian Moment Matching for Parameter Learning in Sum-Product Networks AISTATS 2016
Online Relative Entropy Policy Search using Reproducing Kernel Hilbert Space Embeddings AISTATS 2016
Online Algorithms for Sum-Product Networks with Continuous Variables PGM 2016
Dynamic Sum Product Networks for Tractable Inference on Sequence Data PGM 2016
Overfitting at SemEval-2016 Task 3: Detecting Semantically Similar Questions in Community Question Answering Forums with Word Embeddings SEMEVAL 2016
A Unified Approach for Learning the Parameters of Sum-Product Networks NIPS 2016
Online Bayesian Moment Matching for Topic Modeling with Unknown Number of Topics NIPS 2016
Self-Adaptive Hierarchical Sentence Model IJCAI 2015
On the Relationship between Sum-Product Networks and Bayesian Networks ICML 2015
Learning Community-Based Preferences via Dirichlet Process Mixtures of Gaussian Processes IJCAI 2013
Isomorph-Free Branch and Bound Search for Finite State Controllers IJCAI 2013
Cost-Sensitive Exploration in Bayesian Reinforcement Learning NIPS 2012
Symbolic Dynamic Programming for Continuous State and Observation POMDPs NIPS 2012
Asymptotic Theory for Linear-Chain Conditional Random Fields AISTATS 2011
Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints NIPS 2011
Generating Lexical Analogies Using Dependency Relations CONLL 2007
Generating Lexical Analogies Using Dependency Relations EMNLP 2007
Point-Based Value Iteration for Continuous POMDPs JMLR 2006
Automated Hierarchy Discovery for Planning in Partially Observable Environments NIPS 2006