Youzhi Luo
14 papers · 2021–2025 · 5 conferences · across top CS/AI conferences
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Conferences
ICML (5)
NIPS (4)
ICLR (3)
AAAI (1)
JMLR (1)
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Keywords
graph neural network
(4)
drug discovery
(2)
3d molecule generation
(2)
self-supervised learning
(1)
geometric deep learning
(1)
graph structure
(1)
adversarial training
(1)
out-of-distribution generalization
(1)
machine learning
(1)
disentangled representation
(1)
normalizing flow
(1)
variational autoencoder
(1)
latent space
(1)
molecular dynamics
(1)
imbalanced classification
(1)
deep learning
(1)
molecular design
(1)
discrete latent variable
(1)
molecule generation
(1)
graph generation
(1)
Papers
Geometry Informed Tokenization of Molecules for Language Model Generation
ICML 2025
Learning Disentangled Equivariant Representation for Explicitly Controllable 3D Molecule Generation
AAAI 2025
Graph Structure Extrapolation for Out-of-Distribution Generalization
ICML 2024
Automated Data Augmentations for Graph Classification
ICLR 2023
Learning Fair Graph Representations via Automated Data Augmentations
ICLR 2023
Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization
NIPS 2023
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction
ICML 2023
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules
NIPS 2023
Towards Symmetry-Aware Generation of Periodic Materials
NIPS 2023
Generating 3D Molecules for Target Protein Binding
ICML 2022
An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch
ICLR 2022
DIG: A Turnkey Library for Diving into Graph Deep Learning Research
JMLR 2021
GraphDF: A Discrete Flow Model for Molecular Graph Generation
ICML 2021
Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence
NIPS 2021