Youzhi Luo

According to our database1, Youzhi Luo authored at least 19 papers between 2020 and 2023.

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Bibliography

2023
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.
CoRR, 2023

Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization.
CoRR, 2023

3D Molecular Geometry Analysis with 2D Graphs.
CoRR, 2023

QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Towards Symmetry-Aware Generation of Periodic Materials.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction.
Proceedings of the International Conference on Machine Learning, 2023

Automated Data Augmentations for Graph Classification.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning Fair Graph Representations via Automated Data Augmentations.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Frontiers of Graph Neural Networks with DIG.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Generating 3D Molecules for Target Protein Binding.
Proceedings of the International Conference on Machine Learning, 2022

An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
DIG: A Turnkey Library for Diving into Graph Deep Learning Research.
J. Mach. Learn. Res., 2021

Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs.
CoRR, 2021

Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks.
CoRR, 2021

Stochastic Optimization of Area Under Precision-Recall Curve for Deep Learning with Provable Convergence.
CoRR, 2021

Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

GraphDF: A Discrete Flow Model for Molecular Graph Generation.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
MoleculeKit: Machine Learning Methods for Molecular Property Prediction and Drug Discovery.
CoRR, 2020


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