Preprints

Simulate Time-integrated Coarse-grained Molecular Dynamics with Geometric Machine Learning.
Xiang Fu*, Tian Xie*, Nathan J. Rebello, Bradley D. Olsen, Tommi Jaakkola.
ICLR DGM4HSD workshop, 2022.
[website] [paper]

Fragment-Based Sequential Translation for Molecular Optimization.
Benson Chen*, Xiang Fu*, Regina Barzilay, Tommi Jaakkola.
NeurIPS AI4Science workshop, 2021.
[paper]

Publications

Crystal Diffusion Variational Autoencoder for Periodic Material Generation.
Tian Xie*, Xiang Fu*, Octavian Ganea*, Regina Barzilay, Tommi Jaakkola.
International Conference on Learning Representations (ICLR), 2022.
Contributed talk, NeurIPS ML4PS workshop, 2021.
[paper] [code]

Learning to Jump from Pixels.
Gabriel Margolis, Tao Chen, Kartik Paigwar, Xiang Fu, Donghyun Kim, Sangbae Kim, Pulkit Agrawal.
Conference on Robot Learning (CoRL), 2021.
Covered at: MIT News, AZoRobotics, The Robot Report
[website] [paper]

Learning Task Informed Abstractions.
Xiang Fu*, Ge Yang*, Pulkit Agrawal, Tommi Jaakkola.
International Conference on Machine Learning (ICML), 2021.
[website] [paper] [code]

Modeling and Analysis of Tagging Networks in Stack Exchange Communities.
Xiang Fu*, Shangdi Yu*, Austin R. Benson.
Journal of Complex Networks, 2020.
[paper] [code]