57 citations · 113 across the 5 of their papers we have counts for
7 papers
Reinforcement Learning for Personalized Drug Discovery and Design for Complex Diseases: A Systems Pharmacology Perspective
Ryan K. Tan, Yang Liu, Lei Xie
Many multi-genic systemic diseases such as neurological disorders, inflammatory diseases, and the majority of cancers do not have effective treatments yet. Reinforcement learning p…
Exploiting Different Levels of Parallelism in the Quantum Control Microarchitecture for Superconducting Qubits
Mengyu Zhang, Lei Xie, Zhenxing Zhang +7
As current Noisy Intermediate Scale Quantum (NISQ) devices suffer from decoherence errors, any delay in the instruction execution of quantum control microarchitecture can lead to t…
CODE-AE: A Coherent De-confounding Autoencoder for Predicting Patient-Specific Drug Response From Cell Line Transcriptomics
Di He, Lei Xie
Accurate and robust prediction of patient's response to drug treatments is critical for developing precision medicine. However, it is often difficult to obtain a sufficient amount…
Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures
Shuo Zhang, Yang Liu, Lei Xie
The prediction of physicochemical properties from molecular structures is a crucial task for artificial intelligence aided molecular design. A growing number of Graph Neural Networ…
A Cross-Level Information Transmission Network for Predicting Phenotype from New Genotype: Application to Cancer Precision Medicine
Di He, Lei Xie
An unsolved fundamental problem in biology and ecology is to predict observable traits (phenotypes) from a new genetic constitution (genotype) of an organism under environmental pe…
Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation
Shuo Zhang, Lei Xie
Graph Neural Networks (GNNs) are powerful to learn the representation of graph-structured data. Most of the GNNs use the message-passing scheme, where the embedding of a node is it…