Tenenbaum, Joshua

21 publications

NeurIPS 2024 Few-Shot Task Learning Through Inverse Generative Modeling Aviv Netanyahu, Yilun Du, Antonia Bronars, Jyothish Pari, Joshua Tenenbaum, Tianmin Shu, Pulkit Agrawal

NeurIPSW 2023 AI for Mathematics: A Cognitive Science Perspective Cedegao Zhang, Katherine Collins, Adrian Weller, Joshua Tenenbaum

NeurIPSW 2023 Building Cooperative Embodied Agents Modularly with Large Language Models Hongxin Zhang, Weihua Du, Jiaming Shan, Qinhong Zhou, Yilun Du, Joshua Tenenbaum, Tianmin Shu, Chuang Gan

NeurIPSW 2023 Compositional Foundation Models for Hierarchical Planning Anurag Ajay, Seungwook Han, Yilun Du, Shuang Li, Abhi Gupta, Tommi Jaakkola, Joshua Tenenbaum, Leslie Kaelbling, Akash Srivastava, Pulkit Agrawal

ICML 2022 Discovering Generalizable Spatial Goal Representations via Graph-Based Active Reward Learning Aviv Netanyahu, Tianmin Shu, Joshua Tenenbaum, Pulkit Agrawal

ICML 2022 Learning Iterative Reasoning Through Energy Minimization Yilun Du, Shuang Li, Joshua Tenenbaum, Igor Mordatch

ICML 2022 Planning with Diffusion for Flexible Behavior Synthesis Michael Janner, Yilun Du, Joshua Tenenbaum, Sergey Levine

ICML 2022 Prompting Decision Transformer for Few-Shot Policy Generalization Mengdi Xu, Yikang Shen, Shun Zhang, Yuchen Lu, Ding Zhao, Joshua Tenenbaum, Chuang Gan

ICML 2021 A Large-Scale Benchmark for Few-Shot Program Induction and Synthesis Ferran Alet, Javier Lopez-Contreras, James Koppel, Maxwell Nye, Armando Solar-Lezama, Tomas Lozano-Perez, Leslie Kaelbling, Joshua Tenenbaum

ICML 2021 AGENT: A Benchmark for Core Psychological Reasoning Tianmin Shu, Abhishek Bhandwaldar, Chuang Gan, Kevin Smith, Shari Liu, Dan Gutfreund, Elizabeth Spelke, Joshua Tenenbaum, Tomer Ullman

ICML 2021 Improved Contrastive Divergence Training of Energy-Based Models Yilun Du, Shuang Li, Joshua Tenenbaum, Igor Mordatch

ICML 2021 Leveraging Language to Learn Program Abstractions and Search Heuristics Lionel Wong, Kevin M Ellis, Joshua Tenenbaum, Jacob Andreas

CoRL 2020 A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects Anthony Simeonov, Yilun Du, Beomjoon Kim, Francois Hogan, Joshua Tenenbaum, Pulkit Agrawal, Alberto Rodriguez

UAI 2020 Learning to Learn Generative Programs with Memoised Wake-Sleep Luke Hewitt, Tuan Anh Le, Joshua Tenenbaum

ICML 2020 Visual Grounding of Learned Physical Models Yunzhu Li, Toru Lin, Kexin Yi, Daniel Bear, Daniel Yamins, Jiajun Wu, Joshua Tenenbaum, Antonio Torralba

CoRL 2019 Entity Abstraction in Visual Model-Based Reinforcement Learning Rishi Veerapaneni, John D. Co-Reyes, Michael Chang, Michael Janner, Chelsea Finn, Jiajun Wu, Joshua Tenenbaum, Sergey Levine

ICML 2019 Infinite Mixture Prototypes for Few-Shot Learning Kelsey Allen, Evan Shelhamer, Hanul Shin, Joshua Tenenbaum

ICML 2019 Learning to Infer Program Sketches Maxwell Nye, Luke Hewitt, Joshua Tenenbaum, Armando Solar-Lezama

ICML 2019 Neurally-Guided Structure Inference Sidi Lu, Jiayuan Mao, Joshua Tenenbaum, Jiajun Wu

ICML 2013 Structure Discovery in Nonparametric Regression Through Compositional Kernel Search David Duvenaud, James Lloyd, Roger Grosse, Joshua Tenenbaum, Ghahramani Zoubin

AISTATS 2009 Exact and Approximate Sampling by Systematic Stochastic Search Vikash Mansinghka, Daniel Roy, Eric Jonas, Joshua Tenenbaum