Denoise Pretraining on Nonequilibrium Molecules for Accurate and
Transferable Neural Potentials

Denoise Pretraining on Nonequilibrium Molecules for Accurate and Transferable Neural Potentials

3 March 2023

Papers citing "Denoise Pretraining on Nonequilibrium Molecules for Accurate and Transferable Neural Potentials"

14 / 14 papers shown

Title
Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling Shuqi Lu Xiaohong Ji Bohang Zhang Lin Yao Siyuan Liu Zhifeng Gao Linfeng Zhang Guolin Ke AI4CE 46 1 0 13 Mar 2025
Pushing the Limits of All-Atom Geometric Graph Neural Networks: Pre-Training, Scaling and Zero-Shot Transfer Zihan Pengmei Zhengyuan Shen Zichen Wang Marcus Collins Huzefa Rangwala AI4CE 28 2 0 29 Oct 2024
Pretraining Graph Transformers with Atom-in-a-Molecule Quantum Properties for Improved ADMET Modeling Alessio Fallani Ramil I. Nugmanov Jose A. Arjona-Medina Jörg Kurt Wegner Alexandre Tkatchenko Kostiantyn Chernichenko MedIm AI4CE 34 0 0 10 Oct 2024
Pre-training with Fractional Denoising to Enhance Molecular Property Prediction Yuyan Ni Shikun Feng Xin Hong Yuancheng Sun Wei-Ying Ma Zhiming Ma Qiwei Ye Yanyan Lan AI4CE 36 10 0 14 Jul 2024
UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning Shikun Feng Yuyan Ni Minghao Li Yanwen Huang Zhiming Ma Wei-Ying Ma Yanyan Lan SSL 49 7 0 15 May 2024
Molecular relaxation by reverse diffusion with time step prediction Khaled Kahouli Stefaan S. P. Hessmann Klaus-Robert Muller Shinichi Nakajima Stefan Gugler Niklas W. A. Gebauer DiffM 41 5 0 16 Apr 2024
Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields Yi-Lun Liao Tess E. Smidt Abhishek Das DiffM AI4CE 37 12 0 14 Mar 2024
Pretraining Strategy for Neural Potentials Zehua Zhang Zijie Li A. Farimani AI4CE 44 0 0 24 Feb 2024
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method Yuyan Ni Shikun Feng Wei-Ying Ma Zhiming Ma Yanyan Lan DiffM AI4CE 32 10 0 03 Nov 2023
SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials Peter K. Eastman P. Behara David L. Dotson Raimondas Galvelis John E. Herr ... J. Chodera Benjamin P. Pritchard Yuanqing Wang Gianni De Fabritiis T. Markland 34 105 0 21 Sep 2022
Improving Molecular Contrastive Learning via Faulty Negative Mitigation and Decomposed Fragment Contrast Yuyang Wang Rishikesh Magar Chen Liang A. Farimani 43 78 0 18 Feb 2022
Crystal Diffusion Variational Autoencoder for Periodic Material Generation Tian Xie Xiang Fu O. Ganea Regina Barzilay Tommi Jaakkola DiffM BDL 212 232 0 12 Oct 2021
Pre-training Molecular Graph Representation with 3D Geometry Shengchao Liu Hanchen Wang Weiyang Liu Joan Lasenby Hongyu Guo Jian Tang 126 302 0 07 Oct 2021
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials Simon L. Batzner Albert Musaelian Lixin Sun Mario Geiger J. Mailoa M. Kornbluth N. Molinari Tess E. Smidt Boris Kozinsky 206 1,240 0 08 Jan 2021