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

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

4 June 2021

Oliver T. Unke

Mihail Bogojeski

Klaus-Robert Muller

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

18 / 18 papers shown

Title
Learning with Exact Invariances in Polynomial Time Ashkan Soleymani B. Tahmasebi Stefanie Jegelka P. Jaillet 65 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 72 3 0 28 Jan 2025
Equivariant Neural Tangent Kernels Philipp Misof Pan Kessel Jan E. Gerken 52 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 32 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 30 3 0 25 Jan 2024
Variational Monte Carlo on a Budget -- Fine-tuning pre-trained Neural Wavefunctions Michael Scherbela Leon Gerard Philipp Grohs 33 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 15 20 0 15 Jun 2023
Knowledge-augmented Deep Learning and Its Applications: A Survey Zijun Cui Tian Gao Kartik Talamadupula Qiang Ji 25 17 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 28 36 0 28 Oct 2022
Structure-based drug design with geometric deep learning Clemens Isert Kenneth Atz G. Schneider 44 104 0 19 Oct 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 39 370 0 05 Aug 2022
Geometric Deep Learning on Molecular Representations Kenneth Atz F. Grisoni G. Schneider AI4CE 30 286 0 26 Jul 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 39 64 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 158 246 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 203 1,238 0 08 Jan 2021
Deep neural network solution of the electronic Schrödinger equation J. Hermann Zeno Schätzle Frank Noé 149 446 0 16 Sep 2019
A General Theory of Equivariant CNNs on Homogeneous Spaces Taco S. Cohen Mario Geiger Maurice Weiler MLT AI4CE 156 308 0 05 Nov 2018