6 citations · 7 across the 4 of their papers we have counts for
4 papers
Optimizing the Noise in Self-Supervised Learning: from Importance Sampling to Noise-Contrastive Estimation
Omar Chehab, Alexandre Gramfort, Aapo Hyvarinen
Self-supervised learning is an increasingly popular approach to unsupervised learning, achieving state-of-the-art results. A prevalent approach consists in contrasting data points…
Binary Independent Component Analysis: A Non-stationarity-based Approach
Antti Hyttinen, Vitória Barin-Pacela, Aapo Hyvärinen
We consider independent component analysis of binary data. While fundamental in practice, this case has been much less developed than ICA for continuous data. We start by assuming…
Adaptive Multi-View ICA: Estimation of noise levels for optimal inference
Hugo Richard, Pierre Ablin, Aapo Hyvärinen +2
We consider a multi-view learning problem known as group independent component analysis (group ICA), where the goal is to recover shared independent sources from many views. The st…
Modeling Shared Responses in Neuroimaging Studies through MultiView ICA
Hugo Richard, Luigi Gresele, Aapo Hyvärinen +3
Group studies involving large cohorts of subjects are important to draw general conclusions about brain functional organization. However, the aggregation of data coming from multip…