191 citations · 452 across the 7 of their papers we have counts for
7 papers
A Note on Learning Rare Events in Molecular Dynamics using LSTM and Transformer
Wenqi Zeng, Siqin Cao, Xuhui Huang +1
Recurrent neural networks for language models like long short-term memory (LSTM) have been utilized as a tool for modeling and predicting long term dynamics of complex stochastic m…
ECKPN: Explicit Class Knowledge Propagation Network for Transductive Few-shot Learning
Chaofan Chen, Xiaoshan Yang, Changsheng Xu +2
Recently, the transductive graph-based methods have achieved great success in the few-shot classification task. However, most existing methods ignore exploring the class-level know…
A Biologically Plausible Supervised Learning Method for Spiking Neural Networks Using the Symmetric STDP Rule
Yunzhe Hao, Xuhui Huang, Meng Dong +1
Spiking neural networks (SNNs) possess energy-efficient potential due to event-based computation. However, supervised training of SNNs remains a challenge as spike activities are n…
Data-Driven Tight Frame for Cryo-EM Image Denoising and Conformational Classification
Yin Xian, Hanlin Gu, Wei Wang +4
The cryo-electron microscope (cryo-EM) is increasingly popular these years. It helps to uncover the biological structures and functions of macromolecules. In this paper, we address…
Hierarchical Nystrom Methods for Constructing Markov State Models for Conformational Dynamics
Yuan Yao, Raymond Z. Cui, Gregory R. Bowman +3
Markov state models (MSMs) have become a popular approach for investigating the conformational dynamics of proteins and other biomolecules. MSMs are typically built from numerous m…
Universal driving structure of self-sustained oscillatory complex networks
Xuhong Liao, Weiming Ye, Xiaodong Huang +6
Recently, self-sustained oscillations in complex networks consisting of nonoscillatory nodes (network oscillators) have attracted great interest in diverse natural and social field…