From the 1 of 3 linked papers with an AI index.
3 papers
cs.LG2026
ZUNA1.1: A more flexible EEG foundation model for Denoising and Super-resolution
Christopher Warner, Jonas Mago, JR Huml +1
The paper presents ZUNA1.1, a 380‑million‑parameter diffusion autoencoder that can denoise and super‑resolve EEG recordings of variable length and channel configurations, outperfor…
stat.ML2026
Computation-Aware Kalman Filtering with Model Selection for Neural Dynamics
JR Huml, Jonathan Wenger, John P. Cunningham
Due to their explicit priors and ability to model uncertainty, Bayesian methods have played a major role in dynamical latent variable modeling of single-cell neural recordings. How…
eess.SP2026
ZUNA: Flexible EEG Superresolution with Position-Aware Diffusion Autoencoders
Christopher Warner, Jonas Mago, JR Huml +2
We present \texttt{ZUNA}, a 380M-parameter masked diffusion autoencoder trained to perform masked channel infilling and superresolution for arbitrary electrode numbers and position…