Search Results for author: Chee-Kong Lee

Found 6 papers, 3 papers with code

An Equivariant Generative Framework for Molecular Graph-Structure Co-Design

no code implementations12 Apr 2023 Zaixi Zhang, Qi Liu, Chee-Kong Lee, Chang-Yu Hsieh, Enhong Chen

Our extensive investigation reveals that the 2D topology and 3D geometry contain intrinsically complementary information in molecule design, and provide new insights into machine learning-based molecule representation and generation.

Drug Discovery Graph Generation +1

Hierarchical Graph Transformer with Adaptive Node Sampling

1 code implementation8 Oct 2022 Zaixi Zhang, Qi Liu, Qingyong Hu, Chee-Kong Lee

The Transformer architecture has achieved remarkable success in a number of domains including natural language processing and computer vision.

Model Inversion Attacks against Graph Neural Networks

no code implementations16 Sep 2022 Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang, Chee-Kong Lee, Enhong Chen

One famous privacy attack against data analysis models is the model inversion attack, which aims to infer sensitive data in the training dataset and leads to great privacy concerns.

Reinforcement Learning (RL)

Motif-based Graph Self-Supervised Learning for Molecular Property Prediction

1 code implementation NeurIPS 2021 Zaixi Zhang, Qi Liu, Hao Wang, Chengqiang Lu, Chee-Kong Lee

To bridge this gap, we propose Motif-based Graph Self-supervised Learning (MGSSL) by introducing a novel self-supervised motif generation framework for GNNs.

Molecular Property Prediction Property Prediction +2

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