Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions

11 October 2021

Stephan Günnemann

Papers citing "Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions"

26 / 26 papers shown

Title
Ab-initio simulation of excited-state potential energy surfaces with transferable deep quantum Monte Carlo Zeno Schätzle P. Szabó Alice Cuzzocrea Frank Noé 35 0 0 25 Mar 2025
Learning Equivariant Non-Local Electron Density Functionals Nicholas Gao Eike Eberhard Stephan Günnemann 20 1 0 10 Oct 2024
MOFFlow: Flow Matching for Structure Prediction of Metal-Organic Frameworks N. Kim Seongsu Kim Minsu Kim Jinkyoo Park Sungsoo Ahn AI4CE 19 0 0 07 Oct 2024
Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations Nicholas Gao Stephan Günnemann 25 4 0 23 May 2024
On Representing Electronic Wave Functions with Sign Equivariant Neural Networks Nicholas Gao Stephan Günnemann 16 2 0 08 Mar 2024
Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space Leo Schwinn David Dobre Sophie Xhonneux Gauthier Gidel Stephan Gunnemann AAML 31 36 0 14 Feb 2024
Sorting Out Quantum Monte Carlo Jack Richter-Powell Luca Thiede Alán Aspuru-Guzik D. Duvenaud 14 1 0 09 Nov 2023
Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo Rui Li Hao-Tong Ye Du Jiang Xuelan Wen Chuwei Wang ... Xiang Li Di He Ji Chen Weiluo Ren Liwei Wang 14 10 0 17 Jul 2023
Variational Monte Carlo on a Budget -- Fine-tuning pre-trained Neural Wavefunctions Michael Scherbela Leon Gerard Philipp Grohs 18 5 0 15 Jul 2023
Generalizing Graph ODE for Learning Complex System Dynamics across Environments Zijie Huang Yizhou Sun Wei Wang CML OOD AI4CE 27 24 0 10 Jul 2023
Uncertainty Estimation for Molecules: Desiderata and Methods Tom Wollschlager Nicholas Gao Bertrand Charpentier Mohamed Amine Ketata Stephan Günnemann 6 9 0 20 Jun 2023
A Score-Based Model for Learning Neural Wavefunctions Xuan Zhang Shenglong Xu Shuiwang Ji DiffM 10 1 0 25 May 2023
Towards a Foundation Model for Neural Network Wavefunctions Michael Scherbela Leon Gerard Philipp Grohs 11 8 0 17 Mar 2023
Ewald-based Long-Range Message Passing for Molecular Graphs Arthur Kosmala Johannes Gasteiger Nicholas Gao Stephan Günnemann 64 25 0 08 Mar 2023
Generalizing Neural Wave Functions Nicholas Gao Stephan Günnemann 6 20 0 08 Feb 2023
Invariance-Aware Randomized Smoothing Certificates Jan Schuchardt Stephan Günnemann AAML 13 2 0 25 Nov 2022
Deep Variational Free Energy Approach to Dense Hydrogen H.-j. Xie Ziqun Li Han Wang Linfeng Zhang Lei Wang 19 6 0 13 Sep 2022
Graph Neural Networks for Molecules Yuyang Wang Zijie Li A. Farimani GNN AI4CE 38 20 0 12 Sep 2022
Ab-initio quantum chemistry with neural-network wavefunctions J. Hermann J. Spencer Kenny Choo Antonio Mezzacapo W. Foulkes David Pfau Giuseppe Carleo Frank Noé AI4CE 15 70 0 26 Aug 2022
Sampling-free Inference for Ab-Initio Potential Energy Surface Networks Nicholas Gao Stephan Günnemann DiffM 22 18 0 30 May 2022
$O(N^2)$ Universal Antisymmetry in Fermionic Neural Networks Tianyu Pang Shuicheng Yan Min-Bin Lin 12 3 0 26 May 2022
Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need? Leon Gerard Michael Scherbela P. Marquetand Philipp Grohs AI4CE 27 34 0 19 May 2022
Electronic excited states in deep variational Monte Carlo M. Entwistle Zeno Schätzle P. A. Erdman Jan Hermann Frank Noé 6 45 0 17 Mar 2022
Solving the electronic Schrödinger equation for multiple nuclear geometries with weight-sharing deep neural networks Michael Scherbela Rafael Reisenhofer Leon Gerard P. Marquetand Philipp Grohs 17 47 0 18 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 183 1,218 0 08 Jan 2021
Deep neural network solution of the electronic Schrödinger equation J. Hermann Zeno Schätzle Frank Noé 133 444 0 16 Sep 2019