1 citations · 2 across the 9 of their papers we have counts for
10 papers
A Language-Guided Multimodal Foundation Model for Zero-Shot and Multi-Task Brain Signal Analysis
Mingzhi Chen, Yiyu Gui, Guibo Luo +1
Brain signal analysis is essential for both neuroscience research and clinical diagnostics, yet current approaches face critical limitations. End-to-end models require task-specifi…
SPOTR: Spatio-temporal Pooling One-Token Reconstruction for Universal Physiological Signal Self-supervised Learning
Yiyu Gui, Mingzhi Chen, Yuesheng Zhu +2
Physiological signals such as EEG, ECG, and PPG are widely used in clinical monitoring. Recent self-supervised learning (SSL) methods offer an attractive way to leverage unlabeled…
MedTS-TTT: Test-Time Training for Medical Time Series Classification
Mingzhi Chen, Yiyu Gui, Guibo Luo
Medical time series (MedTS) signals such as electroencephalography (EEG) and electrocardiography (ECG) support many clinical applications. However, substantial subject-level hetero…
Stronger Normalization-Free Transformers
Mingzhi Chen, Taiming Lu, Jiachen Zhu +2
Although normalization layers have long been viewed as indispensable components of deep learning architectures, the recent introduction of Dynamic Tanh (DyT) has demonstrated that…
Large Processor Chip Model
Kaiyan Chang, Mingzhi Chen, Yunji Chen +40
Computer System Architecture serves as a crucial bridge between software applications and the underlying hardware, encompassing components like compilers, CPUs, coprocessors, and R…
Federated Learning for Medical Image Classification: A Comprehensive Benchmark
Zhekai Zhou, Guibo Luo, Mingzhi Chen +2
The federated learning paradigm is wellsuited for the field of medical image analysis, as it can effectively cope with machine learning on isolated multicenter data while protectin…
Improving EEG Classification Through Randomly Reassembling Original and Generated Data with Transformer-based Diffusion Models
Mingzhi Chen, Yiyu Gui, Yuqi Su +3
Electroencephalogram (EEG) classification has been widely used in various medical and engineering applications, where it is important for understanding brain function, diagnosing d…
EEGMamba: Bidirectional State Space Model with Mixture of Experts for EEG Multi-task Classification
Yiyu Gui, MingZhi Chen, Yuqi Su +2
In recent years, with the development of deep learning, electroencephalogram (EEG) classification networks have achieved certain progress. Transformer-based models can perform well…
MPCPA: Multi-Center Privacy Computing with Predictions Aggregation based on Denoising Diffusion Probabilistic Model
Guibo Luo, Hanwen Zhang, Xiuling Wang +2
Privacy-preserving computing is crucial for multi-center machine learning in many applications such as healthcare and finance. In this paper a Multi-center Privacy Computing framew…
Spectral Clustering with Smooth Tiny Clusters
Hengrui Wang, Yubo Zhang, Mingzhi Chen +1
Spectral clustering is one of the most prominent clustering approaches. The distance-based similarity is the most widely used method for spectral clustering. However, people have a…