1 citations · 1 across the 4 of their papers we have counts for
5 papers
From Perturbation Sensitivity to Sparse Autoencoder Feature Interpretation: An EEG Foundation-Model Case Study
Yucong Cao, Chenqi Li, Tingting Zhu
Sparse autoencoders (SAEs) split a model's internal activity into many sparse units, or latents, and a latent is often named after a concept when removing that concept from the inp…
BioX-Bridge: Model Bridging for Unsupervised Cross-Modal Knowledge Transfer across Biosignals
Chenqi Li, Yu Liu, Timothy Denison +1
Biosignals offer valuable insights into the physiological states of the human body. Although biosignal modalities differ in functionality, signal fidelity, sensor comfort, and cost…
Cross-Subject Mind Decoding from Inaccurate Representations
Yangyang Xu, Bangzhen Liu, Wenqi Shao +3
Decoding stimulus images from fMRI signals has advanced with pre-trained generative models. However, existing methods struggle with cross-subject mappings due to cognitive variabil…
AnchorInv: Few-Shot Class-Incremental Learning of Physiological Signals via Representation Space Guided Inversion
Chenqi Li, Boyan Gao, Gabriel Jones +2
Deep learning models have demonstrated exceptional performance in a variety of real-world applications. These successes are often attributed to strong base models that can generali…
A Survey of Few-Shot Learning for Biomedical Time Series
Chenqi Li, Timothy Denison, Tingting Zhu
Advancements in wearable sensor technologies and the digitization of medical records have contributed to the unprecedented ubiquity of biomedical time series data. Data-driven mode…