8 papers
Cluster emission and its impact on the r-process nucleosynthesis
Natalia Thomas, Silvia Bara, Thomas Elias Cocolios +20
Cluster emission is an exotic decay mode between alpha-decay and fission, in which a parent nucleus emits a cluster of nucleons heavier than an alpha-particle, but lighter than wha…
Unveiling the Structure of Do-Calculus Reasoning via Derivation Graphs
Clément Yvernes, Emilie Devijver, Marianne Clausel +1
The do-calculus defines a general system of inference for interventional queries, allowing causal quantities to be transformed through successive applications of its rules. This pr…
Identifiable Multimodal Causal Representation Learning under Partial Latent Sharing
Manal Benhamza, Marianne Clausel, Myriam Tami
Causal representation learning (CRL) seeks to uncover meaningful latent variables and their corresponding causal structure from high-dimensional observational data. Although its si…
Time Series Correlations and Kolmogorov Complexity: A Hausdorff Dimension Perspective
Boumediene Hamzi, Marianne Clausel, Kamal Dingle +2
Spurious correlations are common in time-series analysis because simple, low-complexity patterns can produce high Pearson correlations even between unrelated series. We argue that…
Adaptive Regime-Switching Forecasts with Distribution-Free Uncertainty: Deep Switching State-Space Models Meet Conformal Prediction
Echo Diyun LU, Charles Findling, Marianne Clausel +3
Regime transitions routinely break stationarity in time series, making calibrated uncertainty as important as point accuracy. We study distribution-free uncertainty for regime-swit…
Identifiability in Causal Abstractions: A Hierarchy of Criteria
Clément Yvernes, Emilie Devijver, Marianne Clausel +1
Identifying the effect of a treatment from observational data typically requires assuming a fully specified causal diagram. However, such diagrams are rarely known in practice, esp…
Ensembles of Probabilistic Regression Trees
Alexandre Seiller, Éric Gaussier, Emilie Devijver +2
Tree-based ensemble methods such as random forests, gradient-boosted trees, and Bayesianadditive regression trees have been successfully used for regression problems in many applic…
Risk prediction of pathological gambling on social media
Angelina Parfenova, Marianne Clausel
This paper addresses the problem of risk prediction on social media data, specifically focusing on the classification of Reddit users as having a pathological gambling disorder. To…