Chang-Yu Hsieh

83 papers A* 4A 1Misc 1Journal 76Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
SynGFN: learning across chemical space with generative flow-based molecular discovery.
Nat. Comput. Sci.
Yuchen Zhu, Shuwang Li, Jihong Chen, Donghai Zhao, Xiaorui Wang, Yitong Li, Yifei Liu, Yue Kong, Beichen Zhang, Chang Liu, Tingjun Hou, Chang-Yu Hsieh
2025 J jnl
A Scalable and Quantum-Accurate Foundation Model for Biomolecular Force Field via Linearly Tensorized Quadrangle Attention.
CoRR
Qun Su, Kai Zhu, Qiaolin Gou, Jintu Zhang, Renling Hu, Yurong Li, Yongze Wang, Hui Zhang, Ziyi You, Linlong Jiang, Yu Kang, Jike Wang, Chang-Yu Hsieh, Tingjun Hou
2025 J jnl
BioScore: A Foundational Scoring Function For Diverse Biomolecular Complexes.
CoRR
Yuchen Zhu, Jihong Chen, Yitong Li, Xiaomin Fang, Xianbin Ye, Jingzhou He, Xujun Zhang, Jingxuan Ge, Chao Shen, Xiaonan Zhang, Tingjun Hou, Chang-Yu Hsieh
2025 J jnl
CONFIDE: Hallucination Assessment for Reliable Biomolecular Structure Prediction and Design.
CoRR
Zijun Gao, Mutian He, Shijia Sun, Hanqun Cao, Jingjie Zhang, Zihao Luo, Xiaorui Wang, Xiaojun Yao, Chang-Yu Hsieh, Chunbin Gu, Pheng-Ann Heng
2025 J jnl
ChargeNet: E(3) Equivariant Graph Attention Network for Atomic Charge Prediction.
J. Chem. Inf. Model.
Qiaolin Gou, Qun Su, Jike Wang, Hui Zhang, Huiyong Sun, Xujun Zhang, Linlong Jiang, Meijing Fang, Yu Kang, Huanxiang Liu, Tingjun Hou, Chang-Yu Hsieh
2025 J jnl
DGMM: A Deep Learning-Genetic Algorithm Framework for Efficient Lead Optimization in Drug Discovery.
J. Chem. Inf. Model.
Jiebin Fang, Churu Mao, Yuchen Zhu, Xiaoming Chen, Yun Huang, Wanjing Ding, Chang-Yu Hsieh, Zhongjun Ma
2025 J jnl
Deep Learning-Driven Insights into Enzyme-Substrate Interaction Discovery.
J. Chem. Inf. Model.
Wenjia Qian, Xiaorui Wang, Yuansheng Huang, Yu Kang, Peichen Pan, Chang-Yu Hsieh, Tingjun Hou
2025 J jnl
Deep lead optimization enveloped in protein pocket and its application in designing potent and selective ligands targeting LTK protein.
Nat. Mac. Intell.
Shicheng Chen, Odin Zhang, Chenran Jiang, Huifeng Zhao, Xujun Zhang, Mengting Chen, Yun Liu, Qun Su, Zhenxing Wu, Xinyue Wang, Wanglin Qu, Yuanyi Ye, Xin Chai, Ning Wang, Tianyue Wang, Yuan An, Guanlin Wu, Qianqian Yang, Jiean Chen, Wei Xie, Haitao Lin, Dan Li, Chang-Yu Hsieh, Yong Huang, Yu Kang, Tingjun Hou, Peichen Pan
2025 J jnl
ECloudGen: leveraging electron clouds as a latent variable to scale up structure-based molecular design.
Nat. Comput. Sci.
Odin Zhang, Jieyu Jin, Zhenxing Wu, Jintu Zhang, Po Yuan, Yuntao Yu, Haitao Lin, Haiyang Zhong, Xujun Zhang, Chenqing Hua, Weibo Zhao, Zhengshuo Zhang, Kejun Ying, Yufei Huang, Huifeng Zhao, Yu Kang, Peichen Pan, Jike Wang, Dong Guo, Shuangjia Zheng, Chang-Yu Hsieh, Tingjun Hou
2025 J jnl
Evaluating Large Language Models in Scientific Discovery.
CoRR
Zhangde Song, Jieyu Lu, Yuanqi Du, Botao Yu, Thomas M. Pruyn, Yue Huang, Kehan Guo, Xiuzhe Luo, Yuanhao Qu, Yi Qu, Yinkai Wang, Haorui Wang, Jeff Guo, Jingru Gan, Parshin Shojaee, Di Luo, Andres M. Bran, Gen Li, Qiyuan Zhao, Shao-Xiong Lennon Luo, Yuxuan Zhang, Xiang Zou, Wanru Zhao, Yifan F. Zhang, Wucheng Zhang, Shunan Zheng, Saiyang Zhang, Sartaaj Takrim Khan, Mahyar Rajabi Kochi, Samantha Paradi-Maropakis, Tony Baltoiu, Fengyu Xie, Tianyang Chen, Kexin Huang, Weiliang Luo, Meijing Fang, Xin Yang, Lixue Cheng, Jiajun He, Soha Hassoun, Xiangliang Zhang, Wei Wang, Chandan K. Reddy, Chao Zhang, Zhiling Zheng, Mengdi Wang, Le Cong, Carla P. Gomes, Chang-Yu Hsieh, Aditya Nandy, Philippe Schwaller, Heather J. Kulik, Haojun Jia, Huan Sun, Seyed Mohamad Moosavi, Chenru Duan
2025 Misc conf
Exploiting Attention-to-Motion via Transformer for Versatile Video Frame Interpolation.
ICASSP
Chee-Kim Gan, Jian-Jiun Ding, Chang-Yu Hsieh, De-Yan Lu
2025 J jnl
Graph Neural Networks in Modern AI-aided Drug Discovery.
CoRR
Odin Zhang, Haitao Lin, Xujun Zhang, Xiaorui Wang, Zhenxing Wu, Qing Ye, Weibo Zhao, Jike Wang, Kejun Ying, Yu Kang, Chang-Yu Hsieh, Tingjun Hou
2025 J jnl
Learning the PTM Code through a Coarse-to-Fine, Mechanism-Aware Framework.
CoRR
Jingjie Zhang, Hanqun Cao, Zijun Gao, Yu Wang, Shaoning Li, Jun Xu, Cheng Tan, Jun Zhu, Chang-Yu Hsieh, Chunbin Gu, Pheng-Ann Heng
2025 J jnl
PepBAN: A Deep Learning Framework with Bilinear Attention and Adversarial Learning for Peptide-Protein Interaction Prediction.
J. Chem. Inf. Model.
Shuaiyan Li, Xiaorui Wang, Yuchen Zhu, Jingxuan Ge, Donghai Zhao, Hongxia Xu, Tingjun Hou, Chang-Yu Hsieh
2025 J jnl
ProtFlow: Fast Protein Sequence Design via Flow Matching on Compressed Protein Language Model Embeddings.
CoRR
Zitai Kong, Yiheng Zhu, Yinlong Xu, Hanjing Zhou, Mingzhe Yin, Jialu Wu, Hongxia Xu, Chang-Yu Hsieh, Tingjun Hou, Jian Wu
2025 J jnl
Syn-MolOpt: a synthesis planning-driven molecular optimization method using data-derived functional reaction templates.
J. Cheminformatics
Xiaodan Yin, Xiaorui Wang, Zhenxing Wu, Qin Li, Yu Kang, Yafeng Deng, Pei Luo, Huanxiang Liu, Guqin Shi, Zheng Wang, Xiaojun Yao, Chang-Yu Hsieh, Tingjun Hou
2025 A* conf
Synergy of GFlowNet and Protein Language Model Makes a Diverse Antibody Designer.
AAAI
Mingze Yin, Hanjing Zhou, Yiheng Zhu, Jialu Wu, Wei Wu, Mingyang Li, Kun Fu, Zheng Wang, Chang-Yu Hsieh, Tingjun Hou, Jian Wu
2024 J jnl
A general model for predicting enzyme functions based on enzymatic reactions.
J. Cheminformatics
Wenjia Qian, Xiaorui Wang, Yu Kang, Peichen Pan, Tingjun Hou, Chang-Yu Hsieh
2024 J jnl
AAVDiff: Experimental Validation of Enhanced Viability and Diversity in Recombinant Adeno-Associated Virus (AAV) Capsids through Diffusion Generation.
CoRR
Lijun Liu, Jiali Yang, Jianfei Song, Xinglin Yang, Lele Niu, Zeqi Cai, Hui Shi, Tingjun Hou, Chang-Yu Hsieh, Weiran Shen, Yafeng Deng
2024 — conf
ADSP: Advanced Dataset for Shadow Processing, Enabling Visible Occluders via Synthesizing Strategy.
ACCV (5)
Chang-Yu Hsieh, Jian-Jiun Ding
2024 J jnl
AttABseq: an attention-based deep learning prediction method for antigen-antibody binding affinity changes based on protein sequences.
Briefings Bioinform.
Ruofan Jin, Qing Ye, Jike Wang, Zheng Cao, Dejun Jiang, Tianyue Wang, Yu Kang, Wanting Xu, Chang-Yu Hsieh, Tingjun Hou
2024 J jnl
Comprehensive assessment of protein loop modeling programs on large-scale datasets: prediction accuracy and efficiency.
Briefings Bioinform.
Tianyue Wang, Langcheng Wang, Xujun Zhang, Chao Shen, Odin Zhang, Jike Wang, Jialu Wu, Ruofan Jin, Donghao Zhou, Shicheng Chen, Liwei Liu, Xiaorui Wang, Chang-Yu Hsieh, Guangyong Chen, Peichen Pan, Yu Kang, Tingjun Hou
2024 J jnl
DEL-Ranking: Ranking-Correction Denoising Framework for Elucidating Molecular Affinities in DNA-Encoded Libraries.
CoRR
Hanqun Cao, Chunbin Gu, Mutian He, Ning Ma, Chang-Yu Hsieh, Pheng-Ann Heng
2024 J jnl
Deep Geometry Handling and Fragment-wise Molecular 3D Graph Generation.
CoRR
Odin Zhang, Yufei Huang, Shichen Cheng, Mengyao Yu, Xujun Zhang, Haitao Lin, Yundian Zeng, Mingyang Wang, Zhenxing Wu, Huifeng Zhao, Zaixi Zhang, Chenqing Hua, Yu Kang, Sunliang Cui, Peichen Pan, Chang-Yu Hsieh, Tingjun Hou
2024 J jnl
Deep Lead Optimization: Leveraging Generative AI for Structural Modification.
CoRR
Odin Zhang, Haitao Lin, Hui Zhang, Huifeng Zhao, Yufei Huang, Yuansheng Huang, Dejun Jiang, Chang-Yu Hsieh, Peichen Pan, Tingjun Hou
2024 J jnl
DrugFlow: An AI-Driven One-Stop Platform for Innovative Drug Discovery.
J. Chem. Inf. Model.
Chao Shen, Jianfei Song, Chang-Yu Hsieh, Dong-Sheng Cao, Yu Kang, Wenling Ye, Zhenxing Wu, Jike Wang, Odin Zhang, Xujun Zhang, Hao Zeng, Heng Cai, Yu Chen, Linkang Chen, Hao Luo, Xinda Zhao, Tianye Jian, Tong Chen, Dejun Jiang, Mingyang Wang, Qing Ye, Jialu Wu, Hongyan Du, Hui Shi, Yafeng Deng, Tingjun Hou
2024 J jnl
Generative AI for Controllable Protein Sequence Design: A Survey.
CoRR
Yiheng Zhu, Zitai Kong, Jialu Wu, Weize Liu, Yuqiang Han, Mingze Yin, Hongxia Xu, Chang-Yu Hsieh, Tingjun Hou
2024 J jnl
Genetic Algorithm-Based Receptor Ligand: A Genetic Algorithm-Guided Generative Model to Boost the Novelty and Drug-Likeness of Molecules in a Sampling Chemical Space.
J. Chem. Inf. Model.
Mingyang Wang, Zhengjian Wu, Jike Wang, Gaoqi Weng, Yu Kang, Peichen Pan, Dan Li, Yafeng Deng, Xiaojun Yao, Zhitong Bing, Chang-Yu Hsieh, Tingjun Hou
2024 J jnl
Human-level molecular optimization driven by mol-gene evolution.
CoRR
Jiebin Fang, Churu Mao, Yuchen Zhu, Xiaoming Chen, Chang-Yu Hsieh, Zhongjun Ma
2024 J jnl
Leveraging language model for advanced multiproperty molecular optimization via prompt engineering.
Nat. Mac. Intell.
Zhenxing Wu, Odin Zhang, Xiaorui Wang, Li Fu, Huifeng Zhao, Jike Wang, Hongyan Du, Dejun Jiang, Yafeng Deng, Dong-Sheng Cao, Chang-Yu Hsieh, Tingjun Hou
2024 J jnl
Multi-Modal CLIP-Informed Protein Editing.
CoRR
Mingze Yin, Hanjing Zhou, Yiheng Zhu, Miao Lin, Yixuan Wu, Jialu Wu, Hongxia Xu, Chang-Yu Hsieh, Tingjun Hou, Jintai Chen, Jian Wu
2024 J jnl
Parallelized variational quantum classifier with shallow QRAM circuit.
Quantum Inf. Process.
Bojia Duan, Xin Sun, Chang-Yu Hsieh
2024 J jnl
S
CoRR
Mingze Yin, Hanjing Zhou, Jialu Wu, Yiheng Zhu, Yuxuan Zhan, Zitai Kong, Hongxia Xu, Chang-Yu Hsieh, Jintai Chen, Tingjun Hou, Jian Wu
2024 J jnl
SynergyX: a multi-modality mutual attention network for interpretable drug synergy prediction.
Briefings Bioinform.
Yue Guo, Haitao Hu, Wenbo Chen, Hao Yin, Jian Wu, Chang-Yu Hsieh, Qiaojun He, Ji Cao
2024 J jnl
Token-Mol 1.0: Tokenized drug design with large language model.
CoRR
Jike Wang, Rui Qin, Mingyang Wang, Meijing Fang, Yangyang Zhang, Yuchen Zhu, Qun Su, Qiaolin Gou, Chao Shen, Odin Zhang, Zhenxing Wu, Dejun Jiang, Xujun Zhang, Huifeng Zhao, Xiaozhe Wan, Zhourui Wu, Liwei Liu, Yu Kang, Chang-Yu Hsieh, Tingjun Hou
2024 J jnl
Unlocking Potential Binders: Multimodal Pretraining DEL-Fusion for Denoising DNA-Encoded Libraries.
CoRR
Chunbin Gu, Mutian He, Hanqun Cao, Guangyong Chen, Chang-Yu Hsieh, Pheng-Ann Heng
2023 J jnl
An Equivariant Generative Framework for Molecular Graph-Structure Co-Design.
CoRR
Zaixi Zhang, Qi Liu, Chee-Kong Lee, Chang-Yu Hsieh, Enhong Chen
2023 J jnl
Deep Generation Model Guided by the Docking Score for Active Molecular Design.
J. Chem. Inf. Model.
Yuwei Yang, Chang-Yu Hsieh, Yu Kang, Tingjun Hou, Huanxiang Liu, Xiaojun Yao
2023 J jnl
Efficient and accurate large library ligand docking with KarmaDock.
Nat. Comput. Sci.
Xujun Zhang, Odin Zhang, Chao Shen, Wanglin Qu, Shicheng Chen, Hanqun Cao, Yu Kang, Zhe Wang, Ercheng Wang, Jintu Zhang, Yafeng Deng, Furui Liu, Tianyue Wang, Hongyan Du, Langcheng Wang, Peichen Pan, Guangyong Chen, Chang-Yu Hsieh, Tingjun Hou
2023 J jnl
From Black Boxes to Actionable Insights: A Perspective on Explainable Artificial Intelligence for Scientific Discovery.
J. Chem. Inf. Model.
Zhenxing Wu, Jihong Chen, Yitong Li, Yafeng Deng, Haitao Zhao, Chang-Yu Hsieh, Tingjun Hou
2023 J jnl
From molecules to scaffolds to functional groups: building context-dependent molecular representation via multi-channel learning.
CoRR
Yue Wan, Jialu Wu, Tingjun Hou, Chang-Yu Hsieh, Xiaowei Jia
2023 J jnl
Improved GNNs for Log 
J. Chem. Inf. Model.
Yanqing Duan, Li Fu, Xiao-Chen Zhang, Teng-Zhi Long, Yuan-Hang He, Zhao-Qian Liu, Ai-Ping Lu, Yafeng Deng, Chang-Yu Hsieh, Tingjun Hou, Dong-Sheng Cao
2023 J jnl
Learning on topological surface and geometric structure for 3D molecular generation.
Nat. Comput. Sci.
Odin Zhang, Tianyue Wang, Gaoqi Weng, Dejun Jiang, Ning Wang, Xiaorui Wang, Huifeng Zhao, Jialu Wu, Ercheng Wang, Guangyong Chen, Yafeng Deng, Peichen Pan, Yu Kang, Chang-Yu Hsieh, Tingjun Hou
2023 A* conf
MolHF: A Hierarchical Normalizing Flow for Molecular Graph Generation.
IJCAI
Yiheng Zhu, Zhenqiu Ouyang, Ben Liao, Jialu Wu, Yixuan Wu, Chang-Yu Hsieh, Tingjun Hou, Jian Wu
2023 J jnl
MolHF: A Hierarchical Normalizing Flow for Molecular Graph Generation.
CoRR
Yiheng Zhu, Zhenqiu Ouyang, Ben Liao, Jialu Wu, Yixuan Wu, Chang-Yu Hsieh, Tingjun Hou, Jian Wu
2023 J jnl
Molecular Generation with Reduced Labeling through Constraint Architecture.
J. Chem. Inf. Model.
Jike Wang, Yundian Zeng, Huiyong Sun, Junmei Wang, Xiaorui Wang, Ruofan Jin, Mingyang Wang, Xujun Zhang, Dong-Sheng Cao, Xi Chen, Chang-Yu Hsieh, Tingjun Hou
2023 J jnl
Protein-Ligand Complex Generator & Drug Screening via Tiered Tensor Transform.
CoRR
Jonathan P. Mailoa, Zhaofeng Ye, Jiezhong Qiu, Chang-Yu Hsieh, Shengyu Zhang
2023 J jnl
ResGen is a pocket-aware 3D molecular generation model based on parallel multiscale modelling.
Nat. Mac. Intell.
Odin Zhang, Jintu Zhang, Jieyu Jin, Xujun Zhang, Renling Hu, Chao Shen, Hanqun Cao, Hongyan Du, Yu Kang, Yafeng Deng, Furui Liu, Guangyong Chen, Chang-Yu Hsieh, Tingjun Hou
2023 A* conf
Sample-efficient Multi-objective Molecular Optimization with GFlowNets.
NeurIPS
Yiheng Zhu, Jialu Wu, Chaowen Hu, Jiahuan Yan, Chang-Yu Hsieh, Tingjun Hou, Jian Wu
2023 J jnl
Sample-efficient Multi-objective Molecular Optimization with GFlowNets.
CoRR
Yiheng Zhu, Jialu Wu, Chaowen Hu, Jiahuan Yan, Chang-Yu Hsieh, Tingjun Hou, Jian Wu
2023 J jnl
TensorCircuit: a Quantum Software Framework for the NISQ Era.
Quantum
Shi-Xin Zhang, Jonathan Allcock, Zhou-Quan Wan, Shuo Liu, Jiace Sun, Hao Yu, Xing-Han Yang, Jiezhong Qiu, Zhaofeng Ye, Yu-Qin Chen, Chee-Kong Lee, Yicong Zheng, Shao-Kai Jian, Hong Yao, Chang-Yu Hsieh, Shengyu Zhang
2022 J jnl
ALipSol: An Attention-Driven Mixture-of-Experts Model for Lipophilicity and Solubility Prediction.
J. Chem. Inf. Model.
Jialu Wu, Junmei Wang, Zhenxing Wu, Shengyu Zhang, Yafeng Deng, Yu Kang, Dong-Sheng Cao, Chang-Yu Hsieh, Tingjun Hou
2022 J jnl
An adaptive graph learning method for automated molecular interactions and properties predictions.
Nat. Mach. Intell.
Yuquan Li, Chang-Yu Hsieh, Ruiqiang Lu, Xiaoqing Gong, Xiaorui Wang, Pengyong Li, Shuo Liu, Yanan Tian, Dejun Jiang, Jiaxian Yan, Qifeng Bai, Huanxiang Liu, Shengyu Zhang, Xiaojun Yao
2022 J jnl
Exploring Low-Toxicity Chemical Space with Deep Learning for Molecular Generation.
J. Chem. Inf. Model.
Yuwei Yang, Zhenxing Wu, Xiaojun Yao, Yu Kang, Tingjun Hou, Chang-Yu Hsieh, Huanxiang Liu
2022 J jnl
Knowledge-based BERT: a method to extract molecular features like computational chemists.
Briefings Bioinform.
Zhenxing Wu, Dejun Jiang, Jike Wang, Xujun Zhang, Hongyan Du, Lurong Pan, Chang-Yu Hsieh, Dongsheng Cao, Tingjun Hou
2022 J jnl
ODBO: Bayesian Optimization with Search Space Prescreening for Directed Protein Evolution.
CoRR
Lixue Cheng, Ziyi Yang, Benben Liao, Chang-Yu Hsieh, Shengyu Zhang
2022 J jnl
Optimizing quantum annealing schedules with Monte Carlo tree search enhanced with neural networks.
Nat. Mach. Intell.
Yu-Qin Chen, Yu Chen, Chee-Kong Lee, Shengyu Zhang, Chang-Yu Hsieh
2022 J jnl
Out-of-the-box deep learning prediction of quantum-mechanical partial charges by graph representation and transfer learning.
Briefings Bioinform.
Dejun Jiang, Huiyong Sun, Jike Wang, Chang-Yu Hsieh, Yuquan Li, Zhenxing Wu, Dong-Sheng Cao, Jian Wu, Tingjun Hou
2022 J jnl
ReMODE: a deep learning-based web server for target-specific drug design.
J. Cheminformatics
Mingyang Wang, Jike Wang, Gaoqi Weng, Yu Kang, Peichen Pan, Dan Li, Yafeng Deng, Honglin Li, Chang-Yu Hsieh, Tingjun Hou
2022 A* conf
Retroformer: Pushing the Limits of End-to-end Retrosynthesis Transformer.
ICML
Yue Wan, Chang-Yu Hsieh, Ben Liao, Shengyu Zhang
2022 J jnl
Retroformer: Pushing the Limits of Interpretable End-to-end Retrosynthesis Transformer.
CoRR
Yue Wan, Benben Liao, Chang-Yu Hsieh, Shengyu Zhang
2022 J jnl
SPLDExtraTrees: robust machine learning approach for predicting kinase inhibitor resistance.
Briefings Bioinform.
Ziyi Yang, Zhaofeng Ye, Yijia Xiao, Chang-Yu Hsieh, Sheng-Yu Zhang
2021 J jnl
ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties.
Nucleic Acids Res.
Guo-Li Xiong, Zhenxing Wu, Jiacai Yi, Li Fu, Zhi-Jiang Yang, Chang-Yu Hsieh, Mingzhu Yin, Xiangxiang Zeng, Chengkun Wu, Aiping Lu, Xiang Chen, Tingjun Hou, Dong-Sheng Cao
2021 J jnl
Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models.
J. Cheminformatics
Dejun Jiang, Zhenxing Wu, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Zhe Wang, Chao Shen, Dong-Sheng Cao, Jian Wu, Tingjun Hou
2021 A conf
Fast Extraction of Word Embedding from Q-contexts.
CIKM
Junsheng Kong, Weizhao Li, Zeyi Liu, Ben Liao, Jiezhong Qiu, Chang-Yu Hsieh, Yi Cai, Shengyu Zhang
2021 J jnl
Fast Extraction of Word Embedding from Q-contexts.
CoRR
Junsheng Kong, Weizhao Li, Zeyi Liu, Ben Liao, Jiezhong Qiu, Chang-Yu Hsieh, Yi Cai, Shengyu Zhang
2021 J jnl
Hyperbolic relational graph convolution networks plus: a simple but highly efficient QSAR-modeling method.
Briefings Bioinform.
Zhenxing Wu, Dejun Jiang, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Dong-Sheng Cao, Tingjun Hou
2021 J jnl
Learning Large-scale Network Embedding from Representative Subgraph.
CoRR
Junsheng Kong, Weizhao Li, Ben Liao, Jiezhong Qiu, Chang-Yu Hsieh, Yi Cai, Jinhui Zhu, Shengyu Zhang
2021 J jnl
MG-BERT: leveraging unsupervised atomic representation learning for molecular property prediction.
Briefings Bioinform.
Xiao-Chen Zhang, Chengkun Wu, Zhi-Jiang Yang, Zhen-Xing Wu, Jiacai Yi, Chang-Yu Hsieh, Tingjun Hou, Dong-Sheng Cao
2021 J jnl
Modeling Protein Using Large-scale Pretrain Language Model.
CoRR
Yijia Xiao, Jiezhong Qiu, Ziang Li, Chang-Yu Hsieh, Jie Tang
2021 J jnl
Multi-constraint molecular generation based on conditional transformer, knowledge distillation and reinforcement learning.
Nat. Mach. Intell.
Jike Wang, Chang-Yu Hsieh, Mingyang Wang, Xiaorui Wang, Zhenxing Wu, Dejun Jiang, Benben Liao, Xujun Zhang, Bo Yang, Qiaojun He, Dongsheng Cao, Xi Chen, Tingjun Hou
2021 J jnl
Neural predictor based quantum architecture search.
Mach. Learn. Sci. Technol.
Shi-Xin Zhang, Chang-Yu Hsieh, Shengyu Zhang, Hong Yao
2021 J jnl
SPLDExtraTrees: Robust machine learning approach for predicting kinase inhibitor resistance.
CoRR
Ziyi Yang, Zhaofeng Ye, Yijia Xiao, Chang-Yu Hsieh
2021 J jnl
TrimNet: learning molecular representation from triplet messages for biomedicine.
Briefings Bioinform.
Pengyong Li, Yuquan Li, Chang-Yu Hsieh, Shengyu Zhang, Xianggen Liu, Huanxiang Liu, Sen Song, Xiaojun Yao
2020 J jnl
A quantum extension of SVM-perf for training nonlinear SVMs in almost linear time.
Quantum
Jonathan Allcock, Chang-Yu Hsieh
2020 J jnl
Quantum Algorithms for Feedforward Neural Networks.
ACM Trans. Quantum Comput.
Jonathan Allcock, Chang-Yu Hsieh, Iordanis Kerenidis, Shengyu Zhang
2020 J jnl
Quantum algorithm for training nonlinear SVMs in almost linear time.
CoRR
Jonathan Allcock, Chang-Yu Hsieh
2019 J jnl
Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models.
CoRR
Guangyong Chen, Pengfei Chen, Chang-Yu Hsieh, Chee-Kong Lee, Benben Liao, Renjie Liao, Weiwen Liu, Jiezhong Qiu, Qiming Sun, Jie Tang, Richard S. Zemel, Shengyu Zhang
2019 J jnl
Rethinking the Usage of Batch Normalization and Dropout in the Training of Deep Neural Networks.
CoRR
Guangyong Chen, Pengfei Chen, Yujun Shi, Chang-Yu Hsieh, Benben Liao, Shengyu Zhang
2019 J jnl
Utilizing Edge Features in Graph Neural Networks via Variational Information Maximization.
CoRR
Pengfei Chen, Weiwen Liu, Chang-Yu Hsieh, Guangyong Chen, Shengyu Zhang
2018 J jnl
Quantum algorithms for feedforward neural networks.
CoRR
Jonathan Allcock, Chang-Yu Hsieh, Iordanis Kerenidis, Shengyu Zhang
2017 J jnl
Resonant transition-based quantum computation.
Quantum Inf. Process.
Chen-Fu Chiang, Chang-Yu Hsieh
2014 J jnl
Correlation Functions in Open Quantum-Classical Systems.
Entropy
Chang-Yu Hsieh, Raymond Kapral