arXiv Machine Learning June 9, 2026 By Jasmeet Singh Bindra, Siddharth Panwar, Shubhajit Roy Chowdhury

How Much Capacity Does EEG Denoising Need? Ultra-Compact Networks reveal Benchmark Saturation and Metric-Utility Gap

Read the original on arXiv Machine Learning →

arXiv:2606. 08594v1 Announce Type: new Abstract: 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 variable or tested whether reconstruction metrics predict downstream neural-signal utility.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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