activity
20222026
most citedContrast Everything: A Hierarchical Contrastive Framework for Medical Time-Series

17 citations · 43 across the 7 of their papers we have counts for

collaborators

7 papers

cs.NE2026★ 1 cited

Benchmarking ERP Analysis: Manual Features, Deep Learning, and Foundation Models

Yihe Wang, Zhiqiao Kang, Bohan Chen +2

Event-related potential (ERP), a specialized paradigm of electroencephalographic (EEG), reflects neurological responses to external stimuli or events, generally associated with the…

cs.LG2025★ 2 cited

LEAD: An EEG Foundation Model for Alzheimer's Disease Detection

Yihe Wang, Nan Huang, Nadia Mammone +2

Electroencephalography (EEG) provides a non-invasive, highly accessible, and cost-effective approach for detecting Alzheimer's disease (AD). However, existing methods, whether base…

cs.CE2024★ 1 cited

What Causes Performance Degradation in Cross-Subject EEG Classification?

Yihe Wang, Taida Li, Yujun Yan +2

Cross-subject Electroencephalography (EEG) classification typically achieves significantly lower performance than subject-dependent settings. Although this phenomenon has been wide…

eess.SP2024★ 2 cited

ADformer: A Multi-Granularity Spatial-Temporal Transformer for EEG-Based Alzheimer Detection

Yihe Wang, Nadia Mammone, Darina Petrovsky +3

Electroencephalography (EEG) has emerged as a cost-effective and efficient tool to support neurologists in the detection of Alzheimer's Disease (AD). However, most existing approac…

eess.SP2024★ 16 cited

Medformer: A Multi-Granularity Patching Transformer for Medical Time-Series Classification

Yihe Wang, Nan Huang, Taida Li +2

Medical time series (MedTS) data, such as Electroencephalography (EEG) and Electrocardiography (ECG), play a crucial role in healthcare, such as diagnosing brain and heart diseases…

cs.LG2023★ 17 cited

Contrast Everything: A Hierarchical Contrastive Framework for Medical Time-Series

Yihe Wang, Yu Han, Haishuai Wang +1

Contrastive representation learning is crucial in medical time series analysis as it alleviates dependency on labor-intensive, domain-specific, and scarce expert annotations. Howev…

cs.CL2022★ 4 cited

Large Language Models are Pretty Good Zero-Shot Video Game Bug Detectors

Mohammad Reza Taesiri, Finlay Macklon, Yihe Wang +2

Video game testing requires game-specific knowledge as well as common sense reasoning about the events in the game. While AI-driven agents can satisfy the first requirement, it is…