| 2025 | ICLR | Learning Equivariant Non-Local Electron Density Functionals. | Nicholas Gao, Eike Eberhard, Stephan Gnnemann |
| 2025 | ICLR | Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space. | Mohamed Amine Ketata, Nicholas Gao, Johanna Sommer, Tom Wollschlger, Stephan Gnnemann |
| 2023 | ICLR | Sampling-free Inference for Ab-Initio Potential Energy Surface Networks. | Nicholas Gao, Stephan Gnnemann |
| 2023 | ICML | Generalizing Neural Wave Functions. | Nicholas Gao, Stephan Gnnemann |
| 2023 | ICML | Ewald-based Long-Range Message Passing for Molecular Graphs. | Arthur Kosmala, Johannes Gasteiger, Nicholas Gao, Stephan Gnnemann |
| 2023 | ICML | Uncertainty Estimation for Molecules: Desiderata and Methods. | Tom Wollschlger, Nicholas Gao, Bertrand Charpentier, Mohamed Amine Ketata, Stephan Gnnemann |
| 2022 | ICLR | Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions. | Nicholas Gao, Stephan Gnnemann |
| 2022 | QCE | Quantum Robustness Verification: A Hybrid Quantum-Classical Neural Network Certification Algorithm. | Nicola Franco, Tom Wollschlger, Nicholas Gao, Jeanette Miriam Lorenz, Stephan Gnnemann |
| 2020 | KDD | High-Dimensional Similarity Search with Quantum-Assisted Variational Autoencoder. | Nicholas Gao, Max Wilson, Thomas Vandal, Walter Vinci, Ramakrishna R. Nemani, Eleanor Gilbert Rieffel |