ML Anthology

Kaelbling, Leslie P.

10 publications

NeurIPS 2023 Compositional Foundation Models for Hierarchical Planning Anurag Ajay, Seungwook Han, Yilun Du, Shuang Li, Abhi Gupta, Tommi Jaakkola, Josh Tenenbaum, Leslie P. Kaelbling, Akash Srivastava, Pulkit Agrawal
NeurIPS 2023 What Planning Problems Can a Relational Neural Network Solve? Jiayuan Mao, Tomás Lozano-Pérez, Josh Tenenbaum, Leslie P. Kaelbling
NeurIPS 2022 PDSketch: Integrated Domain Programming, Learning, and Planning Jiayuan Mao, Tomás Lozano-Pérez, Josh Tenenbaum, Leslie P. Kaelbling
NeurIPS 2021 Tailoring: Encoding Inductive Biases by Optimizing Unsupervised Objectives at Prediction Time Ferran Alet, Maria Bauza, Kenji Kawaguchi, Nurullah Giray Kuru, Tomás Lozano-Pérez, Leslie P. Kaelbling
NeurIPS 2021 Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit Parameterization Clement Gehring, Kenji Kawaguchi, Jiaoyang Huang, Leslie P. Kaelbling
NeurIPS 2020 Adversarially-Learned Inference via an Ensemble of Discrete Undirected Graphical Models Adarsh Keshav Jeewajee, Leslie P. Kaelbling
NeurIPS 2008 Multi-Agent Filtering with Infinitely Nested Beliefs Luke Zettlemoyer, Brian Milch, Leslie P. Kaelbling
NeurIPS 2003 All Learning Is Local: Multi-Agent Learning in Global Reward Games Yu-han Chang, Tracey Ho, Leslie P. Kaelbling
NeurIPS 2003 Approximate Planning in POMDPs with Macro-Actions Georgios Theocharous, Leslie P. Kaelbling
NeurIPS 2003 Envelope-Based Planning in Relational MDPs Natalia H. Gardiol, Leslie P. Kaelbling