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Nicholas Gao
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2020 – today
- 2024
- [i11]Nicholas Gao, Stephan Günnemann:
On Representing Electronic Wave Functions with Sign Equivariant Neural Networks. CoRR abs/2403.05249 (2024) - [i10]Nicholas Gao, Stephan Günnemann:
Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations. CoRR abs/2405.14762 (2024) - [i9]Mohamed Amine Ketata, Nicholas Gao, Johanna Sommer, Tom Wollschläger, Stephan Günnemann:
Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space. CoRR abs/2406.10513 (2024) - 2023
- [c8]Nicholas Gao, Stephan Günnemann:
Sampling-free Inference for Ab-Initio Potential Energy Surface Networks. ICLR 2023 - [c7]Nicholas Gao, Stephan Günnemann:
Generalizing Neural Wave Functions. ICML 2023: 10708-10726 - [c6]Arthur Kosmala, Johannes Gasteiger, Nicholas Gao, Stephan Günnemann:
Ewald-based Long-Range Message Passing for Molecular Graphs. ICML 2023: 17544-17563 - [c5]Tom Wollschläger, Nicholas Gao, Bertrand Charpentier, Mohamed Amine Ketata, Stephan Günnemann:
Uncertainty Estimation for Molecules: Desiderata and Methods. ICML 2023: 37133-37156 - [i8]Nicholas Gao, Stephan Günnemann:
Generalizing Neural Wave Functions. CoRR abs/2302.04168 (2023) - [i7]Arthur Kosmala, Johannes Gasteiger, Nicholas Gao, Stephan Günnemann:
Ewald-based Long-Range Message Passing for Molecular Graphs. CoRR abs/2303.04791 (2023) - [i6]Tom Wollschläger, Nicholas Gao, Bertrand Charpentier, Mohamed Amine Ketata, Stephan Günnemann:
Uncertainty Estimation for Molecules: Desiderata and Methods. CoRR abs/2306.14916 (2023) - [i5]Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian
, Tess E. Smidt, Shuiwang Ji:
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR abs/2307.08423 (2023) - 2022
- [c4]Nicholas Gao, Stephan Günnemann:
Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions. ICLR 2022 - [c3]Nicola Franco, Tom Wollschläger, Nicholas Gao, Jeanette Miriam Lorenz, Stephan Günnemann:
Quantum Robustness Verification: A Hybrid Quantum-Classical Neural Network Certification Algorithm. QCE 2022: 142-153 - [i4]Nicholas Gao, Stephan Günnemann:
Sampling-free Inference for Ab-Initio Potential Energy Surface Networks. CoRR abs/2205.14962 (2022) - 2021
- [i3]Nicholas Gao, Stephan Günnemann:
Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions. CoRR abs/2110.05064 (2021) - 2020
- [c2]Nicholas Gao, Max Wilson, Thomas Vandal, Walter Vinci, Ramakrishna R. Nemani, Eleanor Gilbert Rieffel:
High-Dimensional Similarity Search with Quantum-Assisted Variational Autoencoder. KDD 2020: 956-964 - [c1]Oleksandr Shchur, Nicholas Gao, Marin Bilos, Stephan Günnemann:
Fast and Flexible Temporal Point Processes with Triangular Maps. NeurIPS 2020 - [i2]Nicholas Gao, Max Wilson, Thomas Vandal, Walter Vinci, Ramakrishna R. Nemani, Eleanor Gilbert Rieffel:
High-Dimensional Similarity Search with Quantum-Assisted Variational Autoencoder. CoRR abs/2006.07680 (2020) - [i1]Oleksandr Shchur, Nicholas Gao, Marin Bilos, Stephan Günnemann:
Fast and Flexible Temporal Point Processes with Triangular Maps. CoRR abs/2006.12631 (2020)
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