2021 (6 Papers)

EBM-Fold: Fully-Differentiable Protein Folding Powered by Energy-based Models

Jiaxiang Wu Shitong Luo Tao Shen Haidong Lan Sheng Wang Junzhou Huang

arXiv Preprint: 2105.04771 [cs.LG] 2021

Applying our gradients field method (Shi*, Luo*, et al., ICML'21) to protein folding.

Denoising Gradient Fields for Point Clouds

Shitong Luo Wei Hu

Submitted to ICCV 2021

Learning gradient fields for effective and robust point cloud denoising and beyond.

Learning Gradient Fields for Molecular Conformation Generation

Chence Shi* Shitong Luo* Minkai Xu Jian Tang (* indicates equal contribution)

International Conference on Machine Learning (ICML) 2021 Long Talk

End-to-end conformation sampling; Equivariant score matching.

An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming

Minkai Xu Wujie Wang Shitong Luo Chence Shi Yoshua Bengio Rafael Gomez-Bombarelli Jian Tang

International Conference on Machine Learning (ICML) 2021

Diffusion Probabilistic Models for 3D Point Cloud Generation

Shitong Luo Wei Hu

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021 Oral Best Paper Candidate

Inspired by the diffusion process in non-equilibrium thermodynamics; Markov chain; Competitive performance in generation and auto-encoding.

Learning Neural Generative Dynamics for Molecular Conformation Generation

Minkai Xu* Shitong Luo* Yoshua Bengio Jian Peng Jian Tang (* indicates equal contribution)

International Conference on Learning Representations (ICLR) 2021

Flow-based model for molecular conformation generation; Generating inter-atomic distances to preserve roto-translational invariance; High diversity and fidelity.

2020 (1 Paper)

Differentiable Manifold Reconstruction for Point Cloud Denoising

Shitong Luo Wei Hu

ACM International Conference on Multimedia (ACM MM) 2020 Oral

Neural network architecture for point cloud denoising; Achieving state-of-the-art-performance; Surface-fitting based; Downsample-upsample scheme; Robust against high noise.