| Artificial intelligence for science in quantum, atomistic, and continuum systems X Zhang, L Wang, J Helwig, Y Luo, C Fu, Y Xie, M Liu, Y Lin, Z Xu, K Yan, ... arXiv preprint arXiv:2307.08423, 2023 | 136 | 2023 |
| Neural network ansatz for periodic wave functions and the homogeneous electron gas M Wilson, S Moroni, M Holzmann, N Gao, F Wudarski, T Vegge, ... Physical Review B 107 (23), 235139, 2023 | 55* | 2023 |
| Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions N Gao, S Günnemann International Conference on Learning Representations (Spotlight), 2022 | 45 | 2022 |
| Fast and flexible temporal point processes with triangular maps O Shchur, N Gao, M Biloš, S Günnemann Advances in neural information processing systems (Oral) 33, 73-84, 2020 | 41 | 2020 |
| Ewald-based Long-Range Message Passing for Molecular Graphs A Kosmala, J Gasteiger, N Gao, S Günnemann International Conference on Machine Learning, 2023 | 36 | 2023 |
| Simulations of state-of-the-art fermionic neural network wave functions with diffusion Monte Carlo M Wilson, N Gao, F Wudarski, E Rieffel, NM Tubman Preprint, 2021 | 30 | 2021 |
| Generalizing Neural Wave Functions N Gao, S Günnemann International Conference on Machine Learning, 2023 | 26 | 2023 |
| High-dimensional similarity search with quantum-assisted variational autoencoder N Gao, M Wilson, T Vandal, W Vinci, R Nemani, E Rieffel Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 23 | 2020 |
| Sampling-free Inference for Ab-Initio Potential Energy Surface Networks N Gao, S Günnemann International Conference on Learning Representations, 2023 | 20 | 2023 |
| Quantum robustness verification: A hybrid quantum-classical neural network certification algorithm N Franco, T Wollschläger, N Gao, JM Lorenz, S Günnemann 2022 IEEE International Conference on Quantum Computing and Engineering (QCE …, 2022 | 17 | 2022 |
| Uncertainty estimation for molecules: Desiderata and methods T Wollschläger, N Gao, B Charpentier, MA Ketata, S Günnemann International conference on machine learning, 37133-37156, 2023 | 12 | 2023 |
| Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations N Gao, S Günnemann Neural Information Processing Systems (Oral), 2024 | 4 | 2024 |
| Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space MA Ketata, N Gao, J Sommer, T Wollschläger, S Günnemann ICLR 2025, GRaM @ ICML 2024 (Best Paper Runner-up), 2024 | 1 | 2024 |
| On Representing Electronic Wave Functions with Sign Equivariant Neural Networks N Gao, S Günnemann AI4DifferentialEquations in Science at ICLR, 2024 | 1 | 2024 |
| Learning Equivariant Non-Local Electron Density Functionals N Gao, E Eberhard, S Günnemann ICLR 2025 (Spotlight), 2024 | | 2024 |
| On Learning Quasi-Lagrangian Turbulence AP Toshev, T Kalinov, N Gao, S Günnemann, NA Adams ICLR 2025 Workshop on Machine Learning Multiscale Processes, 0 | | |
Stephan GünnemannProfessor of Computer Science, Technical University of MunichVerified email at in.tum.de
