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Xianhan Tan

2 accepted papers

2025

CRRL: Learning Channel-invariant Neural Representations for High-performance Cross-day Decoding

NeurIPS 2025poster

Brain-computer interfaces have shown great potential in motor and speech rehabilitation, but still suffer from low performance stability across days, mostly due to the instabilities in neural signals. These instabilities, partially caused by neuron deaths and electrode shifts, leading to channel-lev…

Cited by 0SourceScholar
2025

DeCorrNet: Enhancing Neural Decoding Performance by Eliminating Correlations in Noise

AAAI 2025technical

Neural decoding, which transforms neural signals into motor commands, plays a key role in brain-computer interfaces (BCIs). Existing neural decoding approaches mainly rely on the assumption of independent noises, which could perform poorly in case the assumption is invalid. However, correlations in…

Cited by 0SourcePDFScholar