Learning ground states of quantum Hamiltonians with graph networks

12 October 2021

Papers citing "Learning ground states of quantum Hamiltonians with graph networks"

7 / 7 papers shown

Title
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
A Score-Based Model for Learning Neural Wavefunctions Xuan Zhang Shenglong Xu Shuiwang Ji DiffM 25 1 0 25 May 2023
Port-metriplectic neural networks: thermodynamics-informed machine learning of complex physical systems Quercus Hernandez Alberto Badías Francisco Chinesta Elías Cueto PINN AI4CE 27 13 0 03 Nov 2022
MultiScale MeshGraphNets Meire Fortunato Tobias Pfaff Peter Wirnsberger Alexander Pritzel Peter W. Battaglia AI4CE 30 68 0 02 Oct 2022
ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs Limei Wang Yi Liu Yu-Ching Lin Hao Liu Shuiwang Ji GNN 38 89 0 17 Jun 2022
Speeding up Learning Quantum States through Group Equivariant Convolutional Quantum Ansätze Han Zheng Zimu Li Junyu Liu Sergii Strelchuk Risi Kondor 53 54 0 14 Dec 2021
Deep neural network solution of the electronic Schrödinger equation J. Hermann Zeno Schätzle Frank Noé 149 446 0 16 Sep 2019