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20202026
most citedEEGDM: Label-Efficient EEG Representation Learning with Generative Diffusion Model

1 citations · 2 across the 15 of their papers we have counts for

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7 papers · 1 filter

cs.LG2026

STEPS: A Temporal Smooth Error Propagation Solver on the Manifolds for Test-Time Adaptation in Time Series Forecasting

Jiaqi Liu, Yifan Ouyang, Zhifei Song +2

Test-Time Adaptation (TTA) aims to improve time series forecasting under distribution shifts by using limited observations revealed during inference. However, forecasting TTA must…

cs.LG2025

NeurIPT: Foundation Model for Neural Interfaces

Zitao Fang, Chenxuan Li, Hongting Zhou +7

Electroencephalography (EEG) has wide-ranging applications, from clinical diagnosis to brain-computer interfaces (BCIs). With the increasing volume and variety of EEG data, there h…

cs.LG2025

Sleep Stage Classification across Heterogeneous EEG/EOG Channels with Multi-Channel Differential Transformer

Benjamin Wei Hao Chin, Yuin Torng Yew, Haocheng Wu +6

Classification of sleep stages is essential for assessing sleep quality and diagnosing sleep disorders. However, manual inspection of EEG characteristics for each stage is time-con…

cs.LG2025★ 1 cited

EEGDM: Label-Efficient EEG Representation Learning with Generative Diffusion Model

Jia Hong Puah, Sim Kuan Goh, Ziwei Zhang +6

Electroencephalography (EEG) is a critical tool for monitoring brain activity and diagnosing neurological disorders such as epilepsy. However, learning meaningful representations f…

cs.LG2025

Neural Parameter Search for Slimmer Fine-Tuned Models and Better Transfer

Guodong Du, Zitao Fang, Jing Li +10

Foundation models and their checkpoints have significantly advanced deep learning, boosting performance across various applications. However, fine-tuned models often struggle outsi…

cs.LG2025

To See a World in a Spark of Neuron: Disentangling Multi-task Interference for Training-free Model Merging

Zitao Fang, Guodong DU, Shuyang Yu +6

Fine-tuning pre-trained models on targeted datasets enhances task-specific performance but often comes at the expense of generalization. Model merging techniques, which integrate m…

cs.LG2020

A Tunnel Gaussian Process Model for Learning Interpretable Flight's Landing Parameters

Sim Kuan Goh, Narendra Pratap Singh, Zhi Jun Lim +1

Approach and landing accidents have resulted in a significant number of hull losses worldwide. Technologies (e.g., instrument landing system) and procedures (e.g., stabilized appro…