Yilun Du

I am a second-year PhD student at MIT EECS, advised by Prof. Leslie Kaelbling and Prof. Tomas Lozano-Perez and Prof. Josh Tenenbuam. Previously, I obtained my bachelor's degree from MIT, worked at OpenAI and FAIR, and got a gold medal at the International Biology Olympiad.

Research Highlights
  • Generative Modeling: energy based models, compositionality, applications of generative models
  • Physical and 3D Scene Understanding: unsupervised object discovery, 3D reconstruction
  • State Estimation: learning long term object state
  • Robotics: multi-step manipulation
  • Reinforcement Learning: multi-agent/model based/unsupervised reinforcement learning
Publications ( show selected / show all by date / show all by topic )

Topics: Generative Modeling / Physical and 3D Scene Understanding / State Estimation / Robotics / Reinforcement Learning (* indicates equal contribution)

Curious Representation for Embodied Intelligence
Yilun Du, Chuang Gan, Phillip Isola

ArXiv Preprint / Paper

3D Shape Generation and Completion through Point-Voxel Diffusion
Linqi Zhou, Yilun Du, Jiajun Wu

ArXiv Preprint / Paper

Improved Contrastive Divergence Training of Energy Based Models
Yilun Du, Shuang Li, Joshua B. Tenenbaum, Igor Mordatch

ICML 2021 / ICLR 2021 EBM Workshop (Oral) / Paper / Project Page

Energy-Based Models for Continual Learning
Shuang Li, Yilun Du, Gido M. van de Ven, Antonio Torralba, Igor Mordatch

ICLR 2021 EBM Workshop (Oral) / Paper / Project Page

Unsupervised Discovery of 3D Physical Objects from Video
Yilun Du, Kevin Smith, Tomer Ulman, Joshua B. Tenenbaum, Jiajun Wu

ICLR 2021 / Paper / Project Page

Learning an Object Based Memory System
Yilun Du, Joshua B. Tenenbaum, Tomas Lozano-Perez, Leslie Kaelbling

ArXiv Preprint / Paper

Neural Radiance Flow for 4D View Synthesis and Video Processing
Yilun Du, Yinan Zhang, Hong-Xing Yu, Joshua B. Tenenbaum, Jiajun Wu

ArXiv Preprint / Paper / Project Page

Compositional Visual Generation with Energy Based Models
Yilun Du, Shuang Li, Igor Mordatch

NeurIPS 2020 (Spotlight) / Paper / Project Page / Code

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

CORL 2020 / Paper

Energy-based models for atomic-resolution protein conformations
Yilun Du, Joshua Meier, Jerry Ma, Rob Fergus, Alexander Rives

ICLR 2020 (Spotlight) / MLCB 2020 (Oral / Travel Award) / Paper / Code

Observational Overfitting in Reinforcement Learning
Xingyou Song, Yiding Jiang, Yilun Du, Behnam Neyshabur

ICLR 2020 / Paper

Model Based Planning with Energy Based Models
Yilun Du, Toru Lin, Igor Mordatch

CORL 2019 / ICML MBRL Workshop 2019 (Oral) / Paper / Code

Implicit Generation and Generalization with Energy Based Models
Yilun Du, Igor Mordatch

NeurIPS 2019 (Spotlight) / Paper / Code / OpenAI Blog

Task-Agnostic Dynamics Priors for Deep Reinforcement Learning
Yilun Du, Karthik Narasimhan

ICML 2019 / Paper / Code

Neural MMO: A massively multiplayer game environment for intelligent agents
Joseph Suarez, Yilun Du, Phillip Isola, Igor Mordatch

AAMAS 2020 / Paper / Code / OpenAI Blog

Learning to Exploit Stability for 3D Scene Parsing
Yilun Du, Zhijian Liu, Hector Basevi, Ales Leonardis, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu

NeurIPS 2018 / Paper