3 citations · 3 across the 6 of their papers we have counts for
6 papers
Multi-View Causal Discovery without Non-Gaussianity: Identifiability and Algorithms
Ambroise Heurtebise, Omar Chehab, Pierre Ablin +2
Causal discovery is a difficult problem that typically relies on strong assumptions on the data-generating model, such as non-Gaussianity. In practice, many modern applications pro…
MVICAD2: Multi-View Independent Component Analysis with Delays and Dilations
Ambroise Heurtebise, Omar Chehab, Pierre Ablin +1
Machine learning techniques in multi-view settings face significant challenges, particularly when integrating heterogeneous data, aligning feature spaces, and managing view-specifi…
MultiView Independent Component Analysis with Delays
Ambroise Heurtebise, Pierre Ablin, Alexandre Gramfort
Linear Independent Component Analysis (ICA) is a blind source separation technique that has been used in various domains to identify independent latent sources from observed signal…
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…
Accelerating likelihood optimization for ICA on real signals
Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort
We study optimization methods for solving the maximum likelihood formulation of independent component analysis (ICA). We consider both the the problem constrained to white signals…
Stochastic algorithms with descent guarantees for ICA
Pierre Ablin, Alexandre Gramfort, Jean-François Cardoso +1
Independent component analysis (ICA) is a widespread data exploration technique, where observed signals are modeled as linear mixtures of independent components. From a machine lea…