2 citations · 2 across the 7 of their papers we have counts for
5 papers · 1 filter
(MPO): Multivariate Polynomial Optimization based on Matrix Product Operators
Niccolò Ciolli, Anders Vestergaard Nørskov, Michael Kastoryano +2
Central to machine learning and signal processing is the ability to perform universal function approximation and learn complex input-output relationships from limited numbers of ob…
Estimating the Event-Related Potential from Few EEG Trials
Anders Vestergaard Nørskov, Kasper Jørgensen, Alexander Neergaard Zahid +1
Event-related potentials (ERP) are measurements of brain activity with wide applications in basic and clinical neuroscience, that are typically estimated using the average of many…
How Low Can You Go? Searching for the Intrinsic Dimensionality of Complex Networks using Metric Node Embeddings
Nikolaos Nakis, Niels Raunkjær Holm, Andreas Lyhne Fiehn +1
Low-dimensional embeddings are essential for machine learning tasks involving graphs, such as node classification, link prediction, community detection, network visualization, and…
Continuous-time Graph Representation with Sequential Survival Process
Abdulkadir Celikkanat, Nikolaos Nakis, Morten Mørup
Over the past two decades, there has been a tremendous increase in the growth of representation learning methods for graphs, with numerous applications across various fields, inclu…
CSLP-AE: A Contrastive Split-Latent Permutation Autoencoder Framework for Zero-Shot Electroencephalography Signal Conversion
Anders Vestergaard Nørskov, Alexander Neergaard Zahid, Morten Mørup
Electroencephalography (EEG) is a prominent non-invasive neuroimaging technique providing insights into brain function. Unfortunately, EEG data exhibit a high degree of noise and v…