Title
From Theory to Practice: Advancing Multi-Robot Path Planning Algorithms and Applications Teng Guo 64 0 0 11 Jun 2025
Reduced-Order Neural Operators: Learning Lagrangian Dynamics on Highly Sparse Graphs Hrishikesh Viswanath Yue Chang Julius Berner Julius Berner Peter Yichen Chen Aniket Bera AI4CE 129 2 0 04 Jul 2024
Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion Weitao Du Jiujiu Chen Xuecang Zhang Zhiming Ma Shengchao Liu DiffM 78 9 0 06 Dec 2023
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials Shengchao Liu Weitao Du Yanjing Li Zhuoxinran Li Zhiling Zheng ... Anima Anandkumar C. Borgs J. Chayes Hongyu Guo Jian Tang AI4CE 79 23 0 15 Jun 2023
A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining Shengchao Liu Weitao Du Zhiming Ma Hongyu Guo Jian Tang 75 33 0 28 May 2023
A Text-guided Protein Design Framework Shengchao Liu Yanjing Li Zhuoxinran Li A. Gitter Yutao Zhu ... Arvind Ramanathan Chaowei Xiao Jian Tang Hongyu Guo Anima Anandkumar 103 64 0 09 Feb 2023
Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets Xingang Peng Shitong Luo Jiaqi Guan Qi Xie Jian-wei Peng Jianzhu Ma 74 187 0 15 May 2022
Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics Albert Musaelian Simon L. Batzner A. Johansson Lixin Sun Cameron J. Owen M. Kornbluth Boris Kozinsky 95 452 0 11 Apr 2022
TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentials Philipp Thölke Gianni De Fabritiis AI4CE 91 196 0 05 Feb 2022
Neural Operator: Learning Maps Between Function Spaces Nikola B. Kovachki Zong-Yi Li Burigede Liu Kamyar Azizzadenesheli K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 117 449 0 19 Aug 2021
E(n) Equivariant Graph Neural Networks Victor Garcia Satorras Emiel Hoogeboom Max Welling 111 1,020 0 19 Feb 2021
Equivariant message passing for the prediction of tensorial properties and molecular spectra Kristof T. Schütt Oliver T. Unke M. Gastegger 110 534 0 05 Feb 2021
Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules Johannes Klicpera Shankari Giri Johannes T. Margraf Stephan Günnemann 79 323 0 28 Nov 2020
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 341 6,480 0 26 Nov 2020
Machine Learning Force Fields Oliver T. Unke Stefan Chmiela H. E. Sauceda M. Gastegger I. Poltavsky Kristof T. Schütt A. Tkatchenko K. Müller AI4CE 109 913 0 14 Oct 2020
OrbNet: Deep Learning for Quantum Chemistry Using Symmetry-Adapted Atomic-Orbital Features Zhuoran Qiao Matthew Welborn Anima Anandkumar F. Manby Thomas F. Miller AI4CE 70 217 0 15 Jul 2020
Improved Protein-ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference Derek Jones Hyojin Kim Xiaohua Zhang A. Zemla Garrett A. Stevenson W. D. Bennett D. Kirshner Sergio E. Wong F. Lightstone Jonathan E. Allen AI4CE 33 193 0 17 May 2020
Neural Operator: Graph Kernel Network for Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar 199 748 0 07 Mar 2020
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 248 2,131 0 08 Oct 2019
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 417 5,111 0 19 Jun 2018
Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds Nathaniel Thomas Tess E. Smidt S. Kearnes Lusann Yang Li Li Kai Kohlhoff Patrick F. Riley 3DPC 95 973 0 22 Feb 2018