Chuang, Kangway V.

8 publications

ICLRW 2025 Efficient Fine-Tuning of Single-Cell Foundation Models Enables Zero-Shot Molecular Perturbation Prediction Sepideh Maleki, Jan-Christian Huetter, David Richmond, Kangway V. Chuang, Gabriele Scalia, Tommaso Biancalani

TMLR 2024 Score-Based Explainability for Graph Representations Ehsan Hajiramezanali, Sepideh Maleki, Max W Shen, Kangway V. Chuang, Tommaso Biancalani, Gabriele Scalia

NeurIPSW 2024 Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction Karina Zadorozhny, Kangway V. Chuang, Bharath Sathappan, Ewan Wallace, Vishnu Sresht, Colin A Grambow

ICML 2023 Improving Graph Generation by Restricting Graph Bandwidth Nathaniel Lee Diamant, Alex M Tseng, Kangway V. Chuang, Tommaso Biancalani, Gabriele Scalia

ICLRW 2023 Improving Graph Generation by Restricting Graph Bandwidth Nathaniel Lee Diamant, Alex M Tseng, Kangway V Chuang, Tommaso Biancalani, Gabriele Scalia

ICMLW 2023 Learning to Explain Hypergraph Neural Networks Sepideh Maleki, Ehsan Hajiramezanali, Gabriele Scalia, Tommaso Biancalani, Kangway V. Chuang

NeurIPSW 2022 A 3D-Shape Similarity-Based Contrastive Approach to Molecular Representation Learning Austin Atsango, Nathaniel Lee Diamant, Ziqing Lu, Tommaso Biancalani, Gabriele Scalia, Kangway V Chuang

NeurIPSW 2022 Deep Fitness Inference for Drug Discovery with Directed Evolution Nathaniel Lee Diamant, Ziqing Lu, Christina Helmling, Kangway V Chuang, Christian Cunningham, Tommaso Biancalani, Gabriele Scalia, Max W Shen