From the 1 of 5 linked papers with an AI index.
5 papers
Leveraging unlabelled data for generalizable neural population decoding
Ximeng Mao, Nanda H. Krishna, Avery Hee-Woon Ryoo +2
The paper presents MOJO, a framework that combines masked autoencoding self‑supervised learning with supervised training for spike‑tokenizing neural decoders, yielding better decod…
Super Apriel: One Checkpoint, Many Speeds
SLAM Labs, :, Oleksiy Ostapenko +13
We release Super Apriel, a 15B-parameter supernet in which every decoder layer provides four trained mixer choices -- Full Attention (FA), Sliding Window Attention (SWA), Kimi Delt…
Leakage and Second-Order Dynamics Improve Hippocampal RNN Replay
Josue Casco-Rodriguez, Nanda H. Krishna, Richard G. Baraniuk
Biological neural networks (like the hippocampus) can internally generate "replay" resembling stimulus-driven activity. Recent computational models of replay use noisy recurrent ne…
Generalizable, real-time neural decoding with hybrid state-space models
Avery Hee-Woon Ryoo, Nanda H. Krishna, Ximeng Mao +4
Real-time decoding of neural activity is central to neuroscience and neurotechnology applications, from closed-loop experiments to brain-computer interfaces, where models are subje…
Sufficient conditions for offline reactivation in recurrent neural networks
Nanda H. Krishna, Colin Bredenberg, Daniel Levenstein +2
During periods of quiescence, such as sleep, neural activity in many brain circuits resembles that observed during periods of task engagement. However, the precise conditions under…