2022

Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets

Xingang Peng Shitong Luo Jiaqi Guan Qi Xie Jian Peng Jianzhu Ma

International Conference on Machine Learning (ICML) 2022

Using equivariant graph neural networks to improve efficiency and molecule quality of our previous structure-based drug design model (Luo et al., NeurIPS'21).

Deep Point Set Resampling via Gradient Fields

Haolan Chen Bi'an Du Shitong Luo Wei Hu

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2022

An extension to score-based point cloud denoising (Luo and Hu, ICCV'21). Applying gradient fields to denoising, upsampling, and meshing.

Equivariant Point Cloud Analysis via Learning Orientations for Message Passing

Shitong Luo* Jiahan Li* Jiaqi Guan* Yufeng Su Chaoran Cheng Jian Peng Jianzhu Ma (* indicates equal contribution)

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022 Oral

Learning virtual orientations for each point. Projecting neighbor points to local orientations before aggregating information from them.

Deep Learning-Guided Optimization of Human Antibody Against SARS-CoV-2 Variants with Broad Neutralization

Sisi Shan* Shitong Luo* Ziqing Yang* Junxian Hong* Yufeng Su* Fan Ding Lili Fu Chenyu Li Peng Chen Jianzhu Ma Xuanling Shi Qi Zhang Bonnie Berger Linqi Zhang Jian Peng (* indicates equal contribution)

Proceedings of the National Academy of Sciences (PNAS) 2022

Spotting candidates with potentially better neuralization in silico using deep learning. Assaying the candidates in vitro in the wet-lab.

2021

A 3D Molecule Generative Model for Structure-Based Drug Design

Shitong Luo Jiaqi Guan Jianzhu Ma Jian Peng

Conference on Neural Information Processing Systems (NeurIPS) 2021

Generating 3D molecules for protein binding sites. Learning the distribution of atom occurence in the 3D space.

Predicting Molecular Conformation via Dynamic Graph Score Matching

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

Conference on Neural Information Processing Systems (NeurIPS) 2021

Physically based generative modeling.

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

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

Technical Report (arXiv) 2021

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

Score-Based Point Cloud Denoising

Shitong Luo Wei Hu

International Conference on Computer Vision (ICCV) 2021

Estimating the score of noisy point distributions 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 Oral / Long Talk

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

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.

2020

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; Surface-fitting; Downsample-upsample scheme; Robust against high noise.