6 papers
Synthesizing Epileptic Seizures: Gaussian Processes for EEG Generation
Nina Moutonnet, Joshua Corneck, Felipe Tobar +1
Reliable seizure detection from electroencephalography (EEG) time series is a high-priority clinical goal, yet the acquisition cost and scarcity of labeled EEG data limit the perfo…
Accelerated training of Gaussian processes using banded square exponential covariances
Emily C. Ehrhardt, Felipe Tobar
We propose a novel approach to computationally efficient GP training based on the observation that square-exponential (SE) covariance matrices contain several off-diagonal entries…
Efficient Gaussian process learning via subspace projections
Elsa Cazelles, Felipe Tobar
We propose a novel training objective for GPs constructed using lower-dimensional linear projections of the data, referred to as \emph{projected likelihood} (PL). We provide a clos…
AI for a Planet Under Pressure
Victor Galaz, Maria Schewenius, Jonathan F. Donges +26
Artificial intelligence (AI) is already driving scientific breakthroughs in a variety of research fields, ranging from the life sciences to mathematics. This raises a critical ques…
Detection of manatee vocalisations using the Audio Spectrogram Transformer
Stefano Schiappacasse, Taco de Wolff, Yann Henaut +3
The Antillean manatee (\emph{Trichechus manatus}) is an endangered herbivorous aquatic mammal whose role as an ecological balancer and umbrella species underscores the importance o…
Asynchronous Graph Generator
Christopher P. Ley, Felipe Tobar
We introduce the asynchronous graph generator (AGG), a novel graph attention network for imputation and prediction of multi-channel time series. Free from recurrent components or a…