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SE(3)-equivariant prediction of molecular wavefunctions and electronic densities

4 June 2021

Oliver T. Unke

Papers citing "SE(3)-equivariant prediction of molecular wavefunctions and electronic densities"

42 / 42 papers shown

Title
High-order Equivariant Flow Matching for Density Functional Theory Hamiltonian Prediction Seongsu Kim N. Kim Dongwoo Kim SungSoo Ahn 49 0 0 24 May 2025
How simple can you go? An off-the-shelf transformer approach to molecular dynamics Max Eissler Tim Korjakow Stefan Ganscha Oliver T. Unke Klaus-Robert Müller Stefan Gugler 127 2 0 03 Mar 2025
Learning with Exact Invariances in Polynomial Time Ashkan Soleymani B. Tahmasebi Stefanie Jegelka Patrick Jaillet 251 0 0 27 Feb 2025
Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems Yunyang Li Zaishuo Xia Lin Huang Xinran Wei Han Yang ... Zun Wang Chang-Shu Liu Jia Zhang Jia Zhang Mark B. Gerstein 161 3 0 26 Feb 2025
Learning local equivariant representations for quantum operators Zhanghao Zhouyin Zixi Gan MingKang Liu S. K. Pandey Linfeng Zhang Qiangqiang Gu 214 5 0 28 Jan 2025
Equivariant Graph Network Approximations of High-Degree Polynomials for Force Field Prediction Zhao Xu Haiyang Yu Montgomery Bohde Shuiwang Ji 89 2 0 06 Nov 2024
E3STO: Orbital Inspired SE(3)-Equivariant Molecular Representation for Electron Density Prediction Ilan Mitnikov Joseph Jacobson 90 0 0 08 Oct 2024
NeuralSCF: Neural network self-consistent fields for density functional theory Feitong Song Ji Feng 70 1 0 22 Jun 2024
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency Yuchao Lin Jacob Helwig Shurui Gui Shuiwang Ji 99 11 0 11 Jun 2024
Equivariant Neural Tangent Kernels Philipp Misof Pan Kessel Jan E. Gerken 220 0 0 10 Jun 2024
Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models Zun Wang Chang-Shu Liu Nianlong Zou He Zhang Xinran Wei Lin Huang Lijun Wu Jia Zhang 76 3 0 06 Jun 2024
Multi-task learning for molecular electronic structure approaching coupled-cluster accuracy Hao Tang Brian Xiao Wenhao He Pero Subasic A. Harutyunyan Yao Wang Fang Liu Haowei Xu Ju Li 74 1 0 09 May 2024
Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction He Zhang Chang-Shu Liu Zun Wang Xinran Wei Siyuan Liu Nanning Zheng Jia Zhang Tie-Yan Liu 73 9 0 14 Mar 2024
Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields Yi-Lun Liao Tess E. Smidt Abhishek Das DiffM AI4CE 63 12 0 14 Mar 2024
Universal Machine Learning Kohn-Sham Hamiltonian for Materials Yang Zhong Hongyu Yu Ji-Hui Yang Xingyu Guo Hongjun Xiang X. Gong 49 19 0 14 Feb 2024
Reducing the Cost of Quantum Chemical Data By Backpropagating Through Density Functional Theory Alexander Mathiasen Hatem Helal Paul Balanca Adam Krzywaniak Ali Parviz Frederik Hvilshoj Bla.zej Banaszewski Carlo Luschi Andrew William Fitzgibbon 74 5 0 06 Feb 2024
Manifold GCN: Diffusion-based Convolutional Neural Network for Manifold-valued Graphs M. Hanik Gabriele Steidl C. V. Tycowicz GNN MedIm 135 3 0 25 Jan 2024
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products Shengjie Luo Tianlang Chen Aditi S. Krishnapriyan 88 26 0 18 Jan 2024
Towards Harmonization of SO(3)-Equivariance and Expressiveness: a Hybrid Deep Learning Framework for Electronic-Structure Hamiltonian Prediction Shi Yin Xinyang Pan Xudong Zhu Tianyu Gao Haochong Zhang Feng Wu Lixin He 93 2 0 01 Jan 2024
Electronic excited states from physically-constrained machine learning Edoardo Cignoni Divya Suman Jigyasa Nigam Lorenzo Cupellini B. Mennucci Michele Ceriotti 63 17 0 01 Nov 2023
Equivariant Matrix Function Neural Networks Ilyes Batatia Lars L. Schaaf Huajie Chen Gábor Csányi Christoph Ortner Felix A. Faber 87 6 0 16 Oct 2023
Variational Monte Carlo on a Budget -- Fine-tuning pre-trained Neural Wavefunctions Michael Scherbela Leon Gerard Philipp Grohs 68 7 0 15 Jul 2023
EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations Yidong Liao Brandon M. Wood Abhishek Das Tess E. Smidt 138 159 0 21 Jun 2023
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules Haiyang Yu Meng Liu Youzhi Luo A. Strasser X. Qian Xiaoning Qian Shuiwang Ji 92 24 0 15 Jun 2023
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian Haiyang Yu Zhao Xu X. Qian Xiaoning Qian Shuiwang Ji 109 30 0 08 Jun 2023
Equivariant Neural Networks for Spin Dynamics Simulations of Itinerant Magnets Y. Miyazaki 29 4 0 05 May 2023
Learning Harmonic Molecular Representations on Riemannian Manifold Yiqun Wang Yuning Shen Shih‐Ya Chen Lihao Wang Fei Ye Hao Zhou 95 12 0 27 Mar 2023
Towards a Foundation Model for Neural Network Wavefunctions Michael Scherbela Leon Gerard Philipp Grohs 107 10 0 17 Mar 2023
Geometric Clifford Algebra Networks David Ruhe Jayesh K. Gupta Steven De Keninck Max Welling Johannes Brandstetter AI4CE 139 38 0 13 Feb 2023
SchNetPack 2.0: A neural network toolbox for atomistic machine learning Kristof T. Schütt Stefaan S. P. Hessmann Niklas W. A. Gebauer Jonas Lederer M. Gastegger 78 65 0 11 Dec 2022
Knowledge-augmented Deep Learning and Its Applications: A Survey Zijun Cui Tian Gao Kartik Talamadupula Qiang Ji 112 20 0 30 Nov 2022
Transferable E(3) equivariant parameterization for Hamiltonian of molecules and solids Yang Zhong Hongyu Yu Mao Su X. Gong H. Xiang 92 42 0 28 Oct 2022
Structure-based drug design with geometric deep learning Clemens Isert Kenneth Atz G. Schneider 95 111 0 19 Oct 2022
Algorithmic Differentiation for Automated Modeling of Machine Learned Force Fields Niklas Schmitz Klaus-Robert Muller Stefan Chmiela AI4CE 77 11 0 25 Aug 2022
Machine Learning 1- and 2-electron reduced density matrices of polymeric molecules D. Pekker Chungwen Liang Sankha Pattanayak S. Mukhopadhyay 22 0 0 09 Aug 2022
Graph neural networks for materials science and chemistry Patrick Reiser Marlen Neubert André Eberhard Luca Torresi Chen Zhou ... Houssam Metni Clint van Hoesel Henrik Schopmans T. Sommer Pascal Friederich GNN AI4CE 125 422 0 05 Aug 2022
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs Yi-Lun Liao Tess E. Smidt 194 246 0 23 Jun 2022
So3krates: Equivariant attention for interactions on arbitrary length-scales in molecular systems J. Frank Oliver T. Unke Klaus-Robert Muller 89 44 0 28 May 2022
Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations Oliver T. Unke M. Stohr Stefan Ganscha Thomas Unterthiner Hartmut Maennel ... Daniel Ahlin M. Gastegger L. M. Sandonas A. Tkatchenko Klaus-Robert Muller AI4CE 70 18 0 17 May 2022
Generative Coarse-Graining of Molecular Conformations Wujie Wang Minkai Xu Chen Cai Benjamin Kurt Miller Tess E. Smidt Yusu Wang Jian Tang Rafael Gómez-Bombarelli 66 36 0 28 Jan 2022
Geometric Deep Learning on Molecular Representations Kenneth Atz F. Grisoni G. Schneider AI4CE 142 309 0 26 Jul 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 115 69 0 02 Jul 2021