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Wenhan Gao

7 accepted papers

2026

GAGA: Gaussianity-Aware Gaussian Approximation for Efficient 3D Molecular Generation

ICLR 2026poster

Gaussian Probability Path based Generative Models (GPPGMs) generate data by reversing a stochastic process that progressively corrupts samples with Gaussian noise. Despite state-of-the-art results in 3D molecular generation, their deployment is hindered by the high cost of long generative trajectori…

Cited by 0SourceScholar
2025

Discretization-invariance? On the Discretization Mismatch Errors in Neural Operators

ICLR 2025poster

In recent years, neural operators have emerged as a prominent approach for learning mappings between function spaces, such as the solution operators of parametric PDEs. A notable example is the Fourier Neural Operator (FNO), which models the integral kernel as a convolution operator and uses the Con…

Cited by 0SourcePDFScholar
2025

RISE: Radius of Influence based Subgraph Extraction for 3D Molecular Graph Explanation

ICML 2025poster

3D Geometric Graph Neural Networks (GNNs) have emerged as transformative tools for modeling molecular data. Despite their predictive power, these models often suffer from limited interpretability, raising concerns for scientific applications that require reliable and transparent insights. While exis…

2025

RL-Guider: Leveraging Historical Decisions and Feedback for Drug Editing with Large Language Models

ACL 2025finding

Recent success of large language models (LLMs) in diverse domains showcases their potential to revolutionize scientific fields, including drug editing. Traditional drug editing relies on iterative conversations with domain experts, refining the drug until the desired property is achieved. This inter…

2024

Empowering Active Learning for 3D Molecular Graphs with Geometric Graph Isomorphism

NeurIPS 2024poster

Molecular learning is pivotal in many real-world applications, such as drug discovery. Supervised learning requires heavy human annotation, which is particularly challenging for molecular data, e.g., the commonly used density functional theory (DFT) is highly computationally expensive. Active learni…

Cited by 1SourcePDFScholar