5 papers
MANAS-2: Constrained Reconstruction for EEG Foundation Models
Arvasu Kulkarni, Aditya Ray Mishra, Jeet Bandhu Lahiri +5
Masked reconstruction is widely used for EEG foundation models, but optimizing reconstruction on low-SNR waveforms does not necessarily produce the most useful latent representatio…
Adaptive Anisotropic Attention for Axis-Structured Signals
Mahir Jain, Parshva Runwal, Aditya Ray Mishra +4
Dense self-attention treats all token pairs as equally plausible before learning, an interaction-isotropic prior that can be mismatched to structured signals. For structured, low s…
How Much Capacity Does EEG Denoising Need? Ultra-Compact Networks reveal Benchmark Saturation and Metric-Utility Gap
Jasmeet Singh Bindra, Siddharth Panwar
Deep learning EEG denoising architectures have scaled from tens of thousands to tens of millions of parameters, yet no prior study has isolated model capacity as the experimental v…
A spectral audit framework reveals task-dependent aperiodic reliance across EEG and ECG deep learning
Jasmeet Singh Bindra, Siddharth Panwar
Deep learning on physiological time series is interpreted through domain-specific features -- oscillatory rhythms in EEG, morphological complexes in ECG -- yet these signals sit at…
PRISM: Exploring Heterogeneous Pretrained EEG Foundation Model Transfer to Clinical Differential Diagnosis
Jeet Bandhu Lahiri, Parshva Runwal, Arvasu Kulkarni +4
EEG foundation models are typically pretrained on narrow-source clinical archives and evaluated on benchmarks from the same ecosystem, leaving unclear whether representations encod…