Aapo Hyvärinen

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Arxiv: Identifiable Multi-View Causal Discovery Without Non-Gaussianity

TMLR: A noise-corrected Langevin algorithm and sampling by half-denoising

Imag Neurosci: Second-order instantaneous causal analysis of spontaneous MEG

ICML2025: Density Ratio Estimation with Conditional Probability Paths

NeuroAI Group at University of Helsinki

NeuroAI (earlier we used the term neuroinformatics) is widely defined as the cross-fertilization of information-processing and mathematical sciences on the one hand, and neural and cognitive sciences on the other.

Our group works on different aspects of NeuroAI related to machine learning. Some examples include:

  • We develop the theory of statistical machine learning, typically unsupervised.
  • We model the visual system in the brain by analyzing the statistical structure of the natural input images.
  • We apply machine learning models on neuroimaging data, in particular MEG.
  • We develop a NeuroAI approach to affective phenomena, in particular human suffering.

The group is located at the department of Computer Science of the University of Helsinki and its leader is Aapo Hyvärinen.