Interface techniques for 3D control of spatial keyframing. - Igor Mordatch; Patrick Coleman; Karan Singh; Ravin Balakrishnan (SIGGRAPH Posters, 2007)

Safe 3D navigation. - George W. Fitzmaurice; Justin Matejka; Igor Mordatch; Azam Khan; Gordon Kurtenbach (SI3D, 2008)

ViewCube: a 3D orientation indicator and controller. - Azam Khan; Igor Mordatch; George W. Fitzmaurice; Justin Matejka; Gordon Kurtenbach (SI3D, 2008)

Multiscale 3D navigation. - James McCrae; Igor Mordatch; Michael Glueck; Azam Khan (SI3D, 2009)

Feature-based locomotion controllers. - Martin de Lasa; Igor Mordatch; Aaron Hertzmann (ACM Trans. Graph., 2010)

Robust physics-based locomotion using low-dimensional planning. - Igor Mordatch; Martin de Lasa; Aaron Hertzmann (ACM Trans. Graph., 2010)

Contact-Invariant Optimization for Hand Manipulation. - Igor Mordatch; Zoran Popovic; Emanuel Todorov (Symposium on Computer Animation, 2012)

Discovery of complex behaviors through contact-invariant optimization. - Igor Mordatch; Emanuel Todorov; Zoran Popovic (ACM Trans. Graph., 2012)

Stylizing animation by example. - Pierre Bénard; Forrester Cole; Michael Kass; Igor Mordatch; James Hegarty; Martin Sebastian Senn; Kurt W. Fleischer; Davide Pesare; Katherine Breeden (ACM Trans. Graph., 2013)

Animating human lower limbs using contact-invariant optimization. - Igor Mordatch; Jack M. Wang; Emanuel Todorov; Vladlen Koltun (ACM Trans. Graph., 2013)

Combining the benefits of function approximation and trajectory optimization. - Igor Mordatch; Emo Todorov (Robotics: Science and Systems, 2014)

Physics-based trajectory optimization for grasping in cluttered environments. - Nikita Kitaev; Igor Mordatch; Sachin Patil; Pieter Abbeel (ICRA, 2015)

Ensemble-CIO: Full-body dynamic motion planning that transfers to physical humanoids. - Igor Mordatch; Kendall Lowrey; Emanuel Todorov (IROS, 2015)

Interactive Control of Diverse Complex Characters with Neural Networks. - Igor Mordatch; Kendall Lowrey; Galen Andrew; Zoran Popovic; Emanuel Todorov (NIPS, 2015)

Automated Discovery and Learning of Complex Movement Behaviors. - Igor Mordatch (2015)

Combining model-based policy search with online model learning for control of physical humanoids. - Igor Mordatch; Nikhil Mishra; Clemens Eppner; Pieter Abbeel (ICRA, 2016)

Transfer from Simulation to Real World through Learning Deep Inverse Dynamics Model. - Paul F. Christiano; Zain Shah; Igor Mordatch; Jonas Schneider 002; Trevor Blackwell; Joshua Tobin; Pieter Abbeel; Wojciech Zaremba (CoRR, 2016)

A Paradigm for Situated and Goal-Driven Language Learning. - Jon Gauthier; Igor Mordatch (CoRR, 2016)

Prediction and Control with Temporal Segment Models. - Nikhil Mishra; Pieter Abbeel; Igor Mordatch (ICML, 2017)

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. - Ryan Lowe; Yi Wu 013; Aviv Tamar; Jean Harb; Pieter Abbeel; Igor Mordatch (NIPS, 2017)

Interpretable and Pedagogical Examples. - Smitha Milli; Pieter Abbeel; Igor Mordatch (CoRR, 2017)

Emergence of Grounded Compositional Language in Multi-Agent Populations. - Igor Mordatch; Pieter Abbeel (AAAI, 2018)

Learning with Opponent-Learning Awareness. - Jakob N. Foerster; Richard Y. Chen; Maruan Al-Shedivat; Shimon Whiteson; Pieter Abbeel; Igor Mordatch (AAMAS, 2018)

Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments. - Maruan Al-Shedivat; Trapit Bansal; Yura Burda; Ilya Sutskever; Igor Mordatch; Pieter Abbeel (ICLR, 2018)

Emergent Complexity via Multi-Agent Competition. - Trapit Bansal; Jakub Pachocki; Szymon Sidor; Ilya Sutskever; Igor Mordatch (ICLR (Poster), 2018)

Concept Learning with Energy-Based Models. - Igor Mordatch (ICLR (Workshop), 2018)

Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines. - Cathy Wu 002; Aravind Rajeswaran; Yan Duan; Vikash Kumar; Alexandre M. Bayen; Sham M. Kakade; Igor Mordatch; Pieter Abbeel (ICLR, 2018)

Model-Based Planning with Energy-Based Models. - Yilun Du; Toru Lin; Igor Mordatch (CoRL, 2019)

Multi-Agent Reinforcement Learning with Multi-Step Generative Models. - Orr Krupnik; Igor Mordatch; Aviv Tamar (CoRL, 2019)

Skill emergence and transfer in multi-agent environments. - Ingmar Kanitscheider; Bowen Baker; Todor M. Markov; Igor Mordatch (GECCO (Companion), 2019)

Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control. - Kendall Lowrey; Aravind Rajeswaran; Sham M. Kakade; Emanuel Todorov; Igor Mordatch (ICLR (Poster), 2019)

Implicit Generation and Modeling with Energy Based Models. - Yilun Du; Igor Mordatch (NeurIPS, 2019)

Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents. - Joseph Suarez; Yilun Du; Phillip Isola; Igor Mordatch (CoRR, 2019)

Implicit Generation and Generalization in Energy-Based Models. - Yilun Du; Igor Mordatch (CoRR, 2019)

Adaptive Online Planning for Continual Lifelong Learning. - Kevin Lu; Igor Mordatch; Pieter Abbeel (CoRR, 2019)

Neural MMO v1.3: A Massively Multiagent Game Environment for Training and Evaluating Neural Networks. - Joseph Suarez; Yilun Du; Igor Mordatch; Phillip Isola (AAMAS, 2020)

Emergent Tool Use From Multi-Agent Autocurricula. - Bowen Baker; Ingmar Kanitscheider; Todor M. Markov; Yi Wu 013; Glenn Powell; Bob McGrew; Igor Mordatch (ICLR, 2020)

One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control. - Wenlong Huang; Igor Mordatch; Deepak Pathak (ICML, 2020)

A Game Theoretic Framework for Model Based Reinforcement Learning. - Aravind Rajeswaran; Igor Mordatch; Vikash Kumar (ICML, 2020)

Compositional Visual Generation with Energy Based Models. - Yilun Du; Shuang Li 013; Igor Mordatch (NeurIPS, 2020)

Gamma-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction. - Michael Janner; Igor Mordatch; Sergey Levine (NeurIPS, 2020)

Compositional Visual Generation and Inference with Energy Based Models. - Yilun Du; Shuang Li 013; Igor Mordatch (CoRR, 2020)

γ-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction. - Michael Janner; Igor Mordatch; Sergey Levine (CoRR, 2020)

Rearrangement: A Challenge for Embodied AI. - Dhruv Batra; Angel X. Chang; Sonia Chernova; Andrew J. Davison; Jia Deng 001; Vladlen Koltun; Sergey Levine; Jitendra Malik; Igor Mordatch; Roozbeh Mottaghi; Manolis Savva; Hao Su 001 (CoRR, 2020)

Energy-Based Models for Continual Learning. - Shuang Li 013; Yilun Du; Gido M. van de Ven; Antonio Torralba 001; Igor Mordatch (CoRR, 2020)

Implicit Behavioral Cloning. - Pete Florence; Corey Lynch; Andy Zeng 001; Oscar A. Ramirez; Ayzaan Wahid; Laura Downs; Adrian Wong; Johnny Lee; Igor Mordatch; Jonathan Tompson (CoRL, 2021)

Reset-Free Lifelong Learning with Skill-Space Planning. - Kevin Lu; Aditya Grover; Pieter Abbeel; Igor Mordatch (ICLR, 2021)

Improved Contrastive Divergence Training of Energy-Based Models. - Yilun Du; Shuang Li 013; Joshua B. Tenenbaum; Igor Mordatch (ICML, 2021)

Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot. - Joel Z. Leibo; Edgar A. Duéñez-Guzmán; Alexander Vezhnevets; John P. Agapiou; Peter Sunehag; Raphael Koster; Jayd Matyas; Charlie Beattie; Igor Mordatch; Thore Graepel (ICML, 2021)

Model-Based Reinforcement Learning via Latent-Space Collocation. - Oleh Rybkin; Chuning Zhu; Anusha Nagabandi; Kostas Daniilidis; Igor Mordatch; Sergey Levine (ICML, 2021)

Decision Transformer: Reinforcement Learning via Sequence Modeling. - Lili Chen; Kevin Lu; Aravind Rajeswaran; Kimin Lee; Aditya Grover; Michael Laskin; Pieter Abbeel; Aravind Srinivas; Igor Mordatch (NeurIPS, 2021)

Unsupervised Learning of Compositional Energy Concepts. - Yilun Du; Shuang Li 013; Yash Sharma 001; Josh Tenenbaum 001; Igor Mordatch (NeurIPS, 2021)

Brax - A Differentiable Physics Engine for Large Scale Rigid Body Simulation. - C. Daniel Freeman; Erik Frey; Anton Raichuk; Sertan Girgin; Igor Mordatch; Olivier Bachem (NeurIPS Datasets and Benchmarks, 2021)

The Neural MMO Platform for Massively Multiagent Research. - Joseph Suarez; Yilun Du; Clare Zhu; Igor Mordatch; Phillip Isola (NeurIPS Datasets and Benchmarks, 2021)

Pretrained Transformers as Universal Computation Engines. - Kevin Lu; Aditya Grover; Pieter Abbeel; Igor Mordatch (CoRR, 2021)

Generalization in Dexterous Manipulation via Geometry-Aware Multi-Task Learning. - Wenlong Huang; Igor Mordatch; Pieter Abbeel; Deepak Pathak (CoRR, 2021)

Frozen Pretrained Transformers as Universal Computation Engines. - Kevin Lu; Aditya Grover; Pieter Abbeel; Igor Mordatch (AAAI, 2022)

Energy-Based Models for Continual Learning. - Shuang Li 013; Yilun Du; Gido van de Ven; Igor Mordatch (CoLLAs, 2022)

Inner Monologue: Embodied Reasoning through Planning with Language Models. - Wenlong Huang; Fei Xia 002; Ted Xiao; Harris Chan; Jacky Liang; Pete Florence; Andy Zeng 001; Jonathan Tompson; Igor Mordatch; Yevgen Chebotar; Pierre Sermanet; Tomas Jackson; et al. (CoRL, 2022)

Learning Iterative Reasoning through Energy Minimization. - Yilun Du; Shuang Li 013; Joshua B. Tenenbaum; Igor Mordatch (ICML, 2022)

Blocks Assemble! Learning to Assemble with Large-Scale Structured Reinforcement Learning. - Seyed Kamyar Seyed Ghasemipour; Satoshi Kataoka; Byron David; Daniel Freeman; Shixiang Shane Gu; Igor Mordatch (ICML, 2022)

Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents. - Wenlong Huang; Pieter Abbeel; Deepak Pathak; Igor Mordatch (ICML, 2022)

Multi-Game Decision Transformers. - Kuang-Huei Lee; Ofir Nachum; Mengjiao Yang 001; Lisa Lee; Daniel Freeman; Sergio Guadarrama; Ian Fischer; Winnie Xu; Eric Jang; Henryk Michalewski; Igor Mordatch (NeurIPS, 2022)

Pre-Trained Language Models for Interactive Decision-Making. - Shuang Li 013; Xavier Puig; Chris Paxton 001; Yilun Du; Clinton Wang; Linxi Fan; Tao Chen 046; De-An Huang; Ekin Akyürek; Anima Anandkumar; Jacob Andreas; Igor Mordatch; et al. (NeurIPS, 2022)

Bi-Manual Manipulation and Attachment via Sim-to-Real Reinforcement Learning. - Satoshi Kataoka; Seyed Kamyar Seyed Ghasemipour; C. Daniel Freeman; Igor Mordatch (CoRR, 2022)

Implicit Offline Reinforcement Learning via Supervised Learning. - Alexandre Piché; Rafael Pardinas; David Vázquez 001; Igor Mordatch; Chris Pal (CoRR, 2022)

FCM: Forgetful Causal Masking Makes Causal Language Models Better Zero-Shot Learners. - Hao Liu 055; Xinyang Geng; Lisa Lee; Igor Mordatch; Sergey Levine; Sharan Narang; Pieter Abbeel (CoRR, 2022)

VeLO: Training Versatile Learned Optimizers by Scaling Up. - Luke Metz; James Harrison; C. Daniel Freeman; Amil Merchant; Lucas Beyer; James Bradbury; Naman Agrawal; Ben Poole; Igor Mordatch; Adam Roberts; Jascha Sohl-Dickstein (CoRR, 2022)

Melting Pot 2.0. - John P. Agapiou; Alexander Sasha Vezhnevets; Edgar A. Duéñez-Guzmán; Jayd Matyas; Yiran Mao; Peter Sunehag; Raphael Köster; Udari Madhushani; Kavya Kopparapu; Ramona Comanescu; DJ Strouse; Michael Bradley Johanson; et al. (CoRR, 2022)

Diversity Through Exclusion (DTE): Niche Identification for Reinforcement Learning through Value-Decomposition. - Peter Sunehag; Alexander Sasha Vezhnevets; Edgar A. Duéñez-Guzmán; Igor Mordatch; Joel Z. Leibo (AAMAS, 2023)

RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control. - Brianna Zitkovich; Tianhe Yu; Sichun Xu; Peng Xu 010; Ted Xiao; Fei Xia 002; Jialin Wu; Paul Wohlhart; Stefan Welker; Ayzaan Wahid; Quan Vuong; Vincent Vanhoucke; et al. (CoRL, 2023)

Composing Ensembles of Pre-trained Models via Iterative Consensus. - Shuang Li 013; Yilun Du; Joshua B. Tenenbaum; Antonio Torralba 001; Igor Mordatch (ICLR, 2023)

PaLM-E: An Embodied Multimodal Language Model. - Danny Driess; Fei Xia 002; Mehdi S. M. Sajjadi; Corey Lynch; Aakanksha Chowdhery; Brian Ichter; Ayzaan Wahid; Jonathan Tompson; Quan Vuong; Tianhe Yu; Wenlong Huang; Yevgen Chebotar; et al. (ICML, 2023)

Multi-Environment Pretraining Enables Transfer to Action Limited Datasets. - David Venuto; Sherry Yang 001; Pieter Abbeel; Doina Precup; Igor Mordatch; Ofir Nachum (ICML, 2023)

Masked Trajectory Models for Prediction, Representation, and Control. - Philipp Wu; Arjun Majumdar; Kevin Stone; Yixin Lin; Igor Mordatch; Pieter Abbeel; Aravind Rajeswaran (ICML, 2023)

Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agents. - Wenlong Huang; Fei Xia 002; Dhruv Shah; Danny Driess; Andy Zeng 001; Yao Lu 006; Pete Florence; Igor Mordatch; Sergey Levine; Karol Hausman; Brian Ichter (NeurIPS, 2023)

RT-1: Robotics Transformer for Real-World Control at Scale. - Anthony Brohan; Noah Brown; Justice Carbajal; Yevgen Chebotar; Joseph Dabis; Chelsea Finn; Keerthana Gopalakrishnan; Karol Hausman; Alexander Herzog; Jasmine Hsu; Julian Ibarz; Brian Ichter; et al. (Robotics: Science and Systems, 2023)

Grounded Decoding: Guiding Text Generation with Grounded Models for Robot Control. - Wenlong Huang; Fei Xia 002; Dhruv Shah; Danny Driess; Andy Zeng 001; Yao Lu 006; Pete Florence; Igor Mordatch; Sergey Levine; Karol Hausman; Brian Ichter (CoRR, 2023)

Bi-Manual Block Assembly via Sim-to-Real Reinforcement Learning. - Satoshi Kataoka; Youngseog Chung; Seyed Kamyar Seyed Ghasemipour; Pannag Sanketi; Shixiang Shane Gu; Igor Mordatch (CoRR, 2023)

Open X-Embodiment: Robotic Learning Datasets and RT-X Models. - Open X.-Embodiment Collaboration; Abhishek Padalkar; Acorn Pooley; Ajinkya Jain; Alex Bewley; Alexander Herzog; Alex Irpan; Alexander Khazatsky; Anant Raj; Anikait Singh; Anthony Brohan; Antonin Raffin; et al. (CoRR, 2023)

Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5? - C. Daniel Freeman; Laura Culp; Aaron Parisi; Maxwell L. Bileschi; Gamaleldin F. Elsayed; Alex Rizkowsky; Isabelle Simpson; Alex Alemi; Azade Nova; Ben Adlam; Bernd Bohnet; Gaurav Mishra; et al. (CoRR, 2023)

Learning and Controlling Silicon Dopant Transitions in Graphene using Scanning Transmission Electron Microscopy. - Max Schwarzer; Jesse Farebrother; Joshua Greaves; Ekin Dogus Cubuk; Rishabh Agarwal; Aaron C. Courville; Marc G. Bellemare; Sergei V. Kalinin; Igor Mordatch; Pablo Samuel Castro; Kevin M. Roccapriore (CoRR, 2023)

Scalable Diffusion for Materials Generation. - Sherry Yang 001; KwangHwan Cho; Amil Merchant; Pieter Abbeel; Dale Schuurmans; Igor Mordatch; Ekin Dogus Cubuk (ICLR, 2024)

Improving Factuality and Reasoning in Language Models through Multiagent Debate. - Yilun Du; Shuang Li 013; Antonio Torralba 001; Joshua B. Tenenbaum; Igor Mordatch (ICML, 2024)

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. - Abby O'Neill; Abdul Rehman; Abhiram Maddukuri; Abhishek Gupta 004; Abhishek Padalkar; Abraham Lee; Acorn Pooley; Agrim Gupta; Ajay Mandlekar; Ajinkya Jain; Albert Tung; Alex Bewley; et al. (ICRA, 2024)

Generative Hierarchical Materials Search. - Sherry Yang 001; Simon L. Batzner; Ruiqi Gao; Muratahan Aykol; Alexander L. Gaunt; Brendan McMorrow; Danilo Jimenez Rezende; Dale Schuurmans; Igor Mordatch; Ekin Dogus Cubuk (NeurIPS, 2024)

Semi-Supervised One Shot Imitation Learning. - Philipp Wu; Kourosh Hakhamaneshi; Yuqing Du; Igor Mordatch; Aravind Rajeswaran; Pieter Abbeel (RLJ, 2024)

Training Language Models on the Knowledge Graph: Insights on Hallucinations and Their Detectability. - Jiri Hron; Laura Culp; Gamaleldin F. Elsayed; Rosanne Liu; Ben Adlam; Maxwell L. Bileschi; Bernd Bohnet; JD Co-Reyes; Noah Fiedel; C. Daniel Freeman; Izzeddin Gur; Kathleen Kenealy; et al. (CoRR, 2024)

Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. - Avi Singh; John D. Co-Reyes; Rishabh Agarwal; Ankesh Anand; Piyush Patil; Xavier Garcia; Peter J. Liu; James Harrison; Jaehoon Lee 001; Kelvin Xu; Aaron T. Parisi; Abhishek Kumar; et al. (Trans. Mach. Learn. Res., 2024)

Multiagent Finetuning: Self Improvement with Diverse Reasoning Chains. - Vighnesh Subramaniam; Yilun Du; Joshua B. Tenenbaum; Antonio Torralba 001; Shuang Li 013; Igor Mordatch (ICLR, 2025)