4 papers
Fixed Point Explainability
Emanuele La Malfa, Jon Vadillo, Marco Molinari +1
This paper introduces a formal notion of fixed point explanations, inspired by the "why regress" principle, to assess, through recursive applications, the stability of the interpla…
False Discovery Rate Control via Bayesian Mirror Statistic
Marco Molinari, Magne Thoresen
Simultaneously performing variable selection and inference in high-dimensional models is an open challenge in statistics and machine learning. The increasing availability of vast a…
Emergent World Representations in OpenVLA
Marco Molinari, Leonardo Nevali, Saharsha Navani +1
Vision Language Action models (VLAs) trained with policy-based reinforcement learning (RL) encode complex behaviors without explicitly modeling environmental dynamics. However, it…
Interpretable Company Similarity with Sparse Autoencoders
Marco Molinari, Victor Shao, Luca Imeneo +4
Determining company similarity is a vital task in finance, underpinning risk management, hedging, and portfolio diversification. Practitioners often rely on sector and industry cla…