9 citations · 9 across the 2 of their papers we have counts for
7 papers
Learning explanations that are hard to vary
Giambattista Parascandolo, Alexander Neitz, Antonio Orvieto +2
In this paper, we investigate the principle that `good explanations are hard to vary' in the context of deep learning. We show that averaging gradients across examples -- akin to a…
Relative gradient optimization of the Jacobian term in unsupervised deep learning
Luigi Gresele, Giancarlo Fissore, Adrián Javaloy +2
Learning expressive probabilistic models correctly describing the data is a ubiquitous problem in machine learning. A popular approach for solving it is mapping the observations in…
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…
Privacy-Preserving Causal Inference via Inverse Probability Weighting
Si Kai Lee, Luigi Gresele, Mijung Park +1
The use of inverse probability weighting (IPW) methods to estimate the causal effect of treatments from observational studies is widespread in econometrics, medicine and social sci…
The Incomplete Rosetta Stone Problem: Identifiability Results for Multi-View Nonlinear ICA
Luigi Gresele, Paul K. Rubenstein, Arash Mehrjou +2
We consider the problem of recovering a common latent source with independent components from multiple views. This applies to settings in which a variable is measured with multiple…
Orthogonal Structure Search for Efficient Causal Discovery from Observational Data
Anant Raj, Luigi Gresele, Michel Besserve +2
The problem of inferring the direct causal parents of a response variable among a large set of explanatory variables is of high practical importance in many disciplines. Recent wor…