9 citations · 11 across the 7 of their papers we have counts for
4 papers · 1 filter
Enhancing Noise Robustness of Parkinson's Disease Telemonitoring via Contrastive Feature Augmentation
Ziming Tang, Chengbin Hou, Tianyu Zhang +3
Parkinson's disease (PD) is one of the most common neurodegenerative disorder. PD telemonitoring emerges as a novel assessment modality enabling self-administered at-home tests of…
MoESD: Unveil Speculative Decoding's Potential for Accelerating Sparse MoE
Zongle Huang, Lei Zhu, Zongyuan Zhan +5
Large Language Models (LLMs) have achieved remarkable success across many applications, with Mixture of Experts (MoE) models demonstrating great potential. Compared to traditional…
Molecular Graph Representation Learning Integrating Large Language Models with Domain-specific Small Models
Tianyu Zhang, Yuxiang Ren, Chengbin Hou +2
Molecular property prediction is a crucial foundation for drug discovery. In recent years, pre-trained deep learning models have been widely applied to this task. Some approaches t…
CGCL: Collaborative Graph Contrastive Learning without Handcrafted Graph Data Augmentations
Tianyu Zhang, Yuxiang Ren, Wenzheng Feng +2
Unsupervised graph representation learning is a non-trivial topic. The success of contrastive methods in the unsupervised representation learning on structured data inspires simila…