4 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…
A noise-corrected Langevin algorithm and sampling by half-denoising
Aapo Hyvärinen
The Langevin algorithm is a classic method for sampling from a given pdf in a real space. In its basic version, it only requires knowledge of the gradient of the log-density, also…
Painful intelligence: What AI can tell us about human suffering
Aapo Hyvärinen
This book uses the modern theory of artificial intelligence (AI) to understand human suffering or mental pain. Both humans and sophisticated AI agents process information about the…
Causal Representation Learning Made Identifiable by Grouping of Observational Variables
Hiroshi Morioka, Aapo Hyvärinen
A topic of great current interest is Causal Representation Learning (CRL), whose goal is to learn a causal model for hidden features in a data-driven manner. Unfortunately, CRL is…