15 citations · 36 across the 5 of their papers we have counts for
5 papers
Non-parametric Causal Discovery for EU Allowances Returns Through the Information Imbalance
Cristiano Salvagnin, Vittorio del Tatto, Maria Elena De Giuli +2
We propose to use a recently introduced non-parametric tool named Differentiable Information Imbalance (DII) to identify variables that are causally related -- potentially through…
Towards a robust approach to infer causality in molecular systems satisfying detailed balance
Vittorio Del Tatto, Debarshi Banerjee, Ali Hassanali +1
The ability to distinguish between correlation and causation of variables in molecular systems remains an interesting and open area of investigation. In this work, we probe causali…
Linear scaling causal discovery from high-dimensional time series by dynamical community detection
Matteo Allione, Vittorio Del Tatto, Alessandro Laio
Understanding which parts of a dynamical system cause each other is extremely relevant in fundamental and applied sciences. However, inferring causal links from observational data,…
Automatic feature selection and weighting in molecular systems using Differentiable Information Imbalance
Romina Wild, Felix Wodaczek, Vittorio Del Tatto +2
Feature selection is essential in the analysis of molecular systems and many other fields, but several uncertainties remain: What is the optimal number of features for a simplified…
Robust inference of causality in high-dimensional dynamical processes from the Information Imbalance of distance ranks
Vittorio Del Tatto, Gianfranco Fortunato, Domenica Bueti +1
We introduce an approach which allows detecting causal relationships between variables for which the time evolution is available. Causality is assessed by a variational scheme base…