Tomás Lozano-Pérez

Differentiable GPU-Parallelized Task and Motion Planning RSS 2025 LLM-Guided Probabilistic Program Induction for POMDP Model Estimation CoRL 2025 Streaming Flow Policy: Simplifying diffusion/flow-matching policies by treating action trajectories as flow trajectories CoRL 2025 Learning Long-Horizon Action Dependencies in Sampling-Based Bilevel Planning CoRL 2024 Partially Observable Task and Motion Planning with Uncertainty and Risk Awareness RSS 2024 Practice Makes Perfect: Planning to Learning Skill Parameter Policies RSS 2024 Set It Up!: Functional Object Arrangement with Compositional Generative Models RSS 2024 Trust the PRoC3S: Solving Long-Horizon Robotics Problems with LLMs and Constraint Satisfaction CoRL 2024 Compositional Diffusion-Based Continuous Constraint Solvers CoRL 2023 Embodied Lifelong Learning for Task and Motion Planning CoRL 2023 Learning Efficient Abstract Planning Models that Choose What to Predict CoRL 2023 Learning Rational Subgoals from Demonstrations and Instructions AAAI 2023 Learning Reusable Manipulation Strategies CoRL 2023 Predicate Invention for Bilevel Planning AAAI 2023 Sequence-Based Plan Feasibility Prediction for Efficient Task and Motion Planning RSS 2023 What Planning Problems Can A Relational Neural Network Solve? NeurIPS 2023 Discovering State and Action Abstractions for Generalized Task and Motion Planning AAAI 2022 Learning Neuro-Symbolic Skills for Bilevel Planning CoRL 2022 PDSketch: Integrated Domain Programming, Learning, and Planning NeurIPS 2022 PG3: Policy-Guided Planning for Generalized Policy Generation IJCAI 2022 SE(3)-Equivariant Relational Rearrangement with Neural Descriptor Fields CoRL 2022 Active Learning of Abstract Plan Feasibility RSS 2021 A large-scale benchmark for few-shot program induction and synthesis ICML 2021 GLIB: Efficient Exploration for Relational Model-Based Reinforcement Learning via Goal-Literal Babbling AAAI 2021 Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks AAAI 2021 Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time NeurIPS 2021 CAMPs: Learning Context-Specific Abstractions for Efficient Planning in Factored MDPs CoRL 2020 Meta-learning curiosity algorithms ICLR 2020 Monte Carlo Tree Search in Continuous Spaces Using Voronoi Optimistic Optimization with Regret Bounds AAAI 2020 Scalable and Probabilistically Complete Planning for Robotic Spatial Extrusion RSS 2020 Adversarial Actor-Critic Method for Task and Motion Planning Problems Using Planning Experience AAAI 2019 Differentiable Algorithm Networks for Composable Robot Learning RSS 2019 Graph Element Networks: adaptive, structured computation and memory ICML 2019 Learning Compact Models for Planning with Exogenous Processes CoRL 2019 Neural Relational Inference with Fast Modular Meta-learning NeurIPS 2019 Adaptable replanning with compressed linear action models for learning from demonstrations CoRL 2018 Finding Frequent Entities in Continuous Data IJCAI 2018 Learning What Information to Give in Partially Observed Domains CoRL 2018 Modular meta-learning CoRL 2018 Provably Safe Robot Navigation with Obstacle Uncertainty RSS 2017 Sample-Based Methods for Factored Task and Motion Planning RSS 2017 Learning to Rank for Synthesizing Planning Heuristics IJCAI 2016 Object-Based World Modeling in Semi-Static Environments with Dependent Dirichlet Process Mixtures IJCAI 2016 Bayesian Optimization with Exponential Convergence NeurIPS 2015 Symbol Acquisition for Probabilistic High-Level Planning IJCAI 2015