2 citations · 3 across the 5 of their papers we have counts for
5 papers
ZUNA1.1: A more flexible EEG foundation model for Denoising and Super-resolution
Christopher Warner, Jonas Mago, JR Huml +1
We introduce ZUNA1.1, a 380M-parameter diffusion autoencoder for flexible EEG signal reconstruction. ZUNA1.1 is capable of reconstructing variable length sequences of up to 30s, wi…
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…
A probabilistic latent variable model for detecting structure in binary data
Christopher Warner, Kiersten Ruda, Friedrich T. Sommer
We introduce a novel, probabilistic binary latent variable model to detect noisy or approximate repeats of patterns in sparse binary data. The model is based on the "Noisy-OR model…
A Model for Image Segmentation in Retina
Christopher Warner, Friedrich T. Sommer
While traditional feed-forward filter models can reproduce the rate responses of retinal ganglion neurons to simple stimuli, they cannot explain why synchrony between spikes is muc…
Energy growth for a nonlinear oscillator coupled to a monochromatic wave
Dmitry Turaev, Christopher Warner, Sergey Zelik
A system consisting of a chaotic (billiard-like) oscillator coupled to a linear wave equation in the three-dimensional space is considered. It is shown that the chaotic behaviour o…