Nicholas Gao

Technical University of Munich — Germany

Materials Science · Physical Sciences

6h-index178citations21works1.12yr avg
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Research Topics

Machine Learning in Materials Science(8), Computational Drug Discovery Methods(4), Advanced Chemical Physics Studies(3), Neural Networks and Applications(3), Quantum Computing Algorithms and Architecture(2)

Publications21 total

An ab initio foundation model of wavefunctions that accurately describes chemical bond breaking
ArXiv.org·2025· 1 citedOpen Access
Accurate Ab-initio Neural-network Solutions to Large-Scale Electronic Structure Problems
arXiv (Cornell University)·2025Open Access
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
Foundations and Trends® in Machine Learning·2025· 6 cited
Learning Equivariant Non-Local Electron Density Functionals
arXiv (Cornell University)·2024Open Access
Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space
arXiv (Cornell University)·2024· 1 citedOpen Access
Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations
arXiv (Cornell University)·2024· 1 citedOpen Access
On Representing Electronic Wave Functions with Sign Equivariant Neural Networks
arXiv (Cornell University)·2024Open Access
Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations
2024
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
arXiv (Cornell University)·2023· 53 citedOpen Access
Neural network ansatz for periodic wave functions and the homogeneous electron gas
Physical review. B./Physical review. B·2023· 49 citedOpen Access
Uncertainty Estimation for Molecules: Desiderata and Methods
arXiv (Cornell University)·2023· 5 citedOpen Access
Ewald-based Long-Range Message Passing for Molecular Graphs
arXiv (Cornell University)·2023· 6 citedOpen Access
Generalizing Neural Wave Functions
arXiv (Cornell University)·2023· 3 citedOpen Access
Quantum Robustness Verification: A Hybrid Quantum-Classical Neural Network Certification Algorithm
2022 IEEE International Conference on Quantum Computing and Engineering (QCE)·2022· 21 cited
Sampling-free Inference for Ab-Initio Potential Energy Surface Networks
arXiv (Cornell University)·2022· 5 citedOpen Access
Quantum Robustness Verification: A Hybrid Quantum-Classical Neural Network Certification Algorithm
arXiv (Cornell University)·2022· 1 citedOpen Access
Wave function Ansatz (but Periodic) Networks and the Homogeneous Electron Gas
arXiv (Cornell University)·2022· 1 citedOpen Access
Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions
arXiv (Cornell University)·2021· 5 citedOpen Access
Simulations of state-of-the-art fermionic neural network wave functions with diffusion Monte Carlo
arXiv (Cornell University)·2021· 8 citedOpen Access
Fast and Flexible Temporal Point Processes with Triangular Maps
arXiv (Cornell University)·2020· 6 citedOpen Access
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Frequent Co-authors

Stephan Günnemann(16), Max Wilson(3), Filip Wudarski(3), Xuan Zhang(2), Limei Wang(2), Jacob Helwig(2), Youzhi Luo(2), Cong Fu(2), Yaochen Xie(2), Yuchao Lin(2), Xu Zhao(2), Keqiang Yan(2), Keir Adams(2), Maurice Weiler(2), Xiner Li(2), Tianfan Fu(2), Yucheng Wang(2), Haiyang Yu(2), Yuqing Xie(2), Alex Strasser(2)