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"

22 / 22 papers shown

Title
Learning with Exact Invariances in Polynomial Time Ashkan Soleymani B. Tahmasebi Stefanie Jegelka Patrick Jaillet 78 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 Bin Shao Mark B. Gerstein 77 0 0 26 Feb 2025
Learning local equivariant representations for quantum operators Zhanghao Zhouyin Zixi Gan MingKang Liu S. K. Pandey Linfeng Zhang Qiangqiang Gu 90 3 0 28 Jan 2025
Equivariant Neural Tangent Kernels Philipp Misof Pan Kessel Jan E. Gerken 64 0 0 10 Jun 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 43 3 0 06 Feb 2024
Manifold GCN: Diffusion-based Convolutional Neural Network for Manifold-valued Graphs M. Hanik Gabriele Steidl C. V. Tycowicz GNN MedIm 36 3 0 25 Jan 2024
Variational Monte Carlo on a Budget -- Fine-tuning pre-trained Neural Wavefunctions Michael Scherbela Leon Gerard Philipp Grohs 35 5 0 15 Jul 2023
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules Haiyang Yu Meng Liu Youzhi Luo A. Strasser X. Qian Xiaoning Qian Shuiwang Ji 18 20 0 15 Jun 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 25 59 0 11 Dec 2022
Knowledge-augmented Deep Learning and Its Applications: A Survey Zijun Cui Tian Gao Kartik Talamadupula Qiang Ji 27 18 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 36 36 0 28 Oct 2022
Structure-based drug design with geometric deep learning Clemens Isert Kenneth Atz G. Schneider 53 104 0 19 Oct 2022
Algorithmic Differentiation for Automated Modeling of Machine Learned Force Fields Niklas Schmitz Klaus-Robert Muller Stefan Chmiela AI4CE 21 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 12 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 50 373 0 05 Aug 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 40 18 0 17 May 2022
Geometric Deep Learning on Molecular Representations Kenneth Atz F. Grisoni G. Schneider AI4CE 34 287 0 26 Jul 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 39 65 0 02 Jul 2021
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects Oliver T. Unke Stefan Chmiela M. Gastegger Kristof T. Schütt H. E. Sauceda K. Müller 177 247 0 01 May 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 233 1,240 0 08 Jan 2021
Deep neural network solution of the electronic Schrödinger equation J. Hermann Zeno Schätzle Frank Noé 149 448 0 16 Sep 2019
A General Theory of Equivariant CNNs on Homogeneous Spaces Taco S. Cohen Mario Geiger Maurice Weiler MLT AI4CE 165 308 0 05 Nov 2018