1. FRANZESE Giulio
  2. FRANZESE Giulio
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FRANZESE Giulio

Report

Franzese, Giulio; Rossi, Simone; Michiardi, Pietro

ALICE: In-context, Zero-shot, Mutual Information Estimation

Submitted to ArXiV, 29 September 2026
Detail
ARXIV
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Report

Ambrogioni, Luca; Franzese, Giulio; Foresti, Alberto; Raya, Gabriel; Nguyen, Bac; Batzolis, Georgios; Takida, Yuhta; Murata, Naoki; Lai, Chieh-Hsin; Mitsufuji, Yuki

From atoms to entropy: Optimal noise allocation for diffusion training in the convex regime

Submitted to ArXiV, 10 July 2026
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Poster / Demo

Wang, Chao; Nepote, Luca; Franzese, Giulio; Michiardi, Pietro

Relative entropy estimation in function space: Theory and applications to trajectory inference

ICML 2026, 43rd International Conference on Machine Learning, 6-11 July 2026, Seoul, South Korea
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Report

Foresti, Alberto; Franzese, Giulio; Michiardi, Pietro; Butakov, Ivan; Tolmachev, Alexander; Frolov, Alexey

Towards diverse and comprehensive benchmarks for mutual information estimation

Submitted to ArXiV, 3 July 2026
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Report

Galeano Munoz, Simon Pedro; Bounoua, Mustapha; Franzese, Giulio; Michiardi, Pietro; Filippone, Maurizio

DIPHINE: Diffusion-based F-ID neural estimator

Submitted to ArXiV, 17 June 2026
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Conference

Galeano Munoz, Simon Pedro; Bounoua, Mustapha; Franzese, Giulio; Michiardi, Pietro; Filippone, Maurizio

TENDE: Transfer entropy neural diffusion estimation

AISTATS 2026, 29th Annual Conference on Artificial Intelligence and Statistics, 2-5 May 2026, Tangier, Morocco
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Conference

Foresti, Alberto; Franzese, Giulio; Michiardi, Pietro

Information estimation with discrete diffusion

ICLR 2026, 14th International Conference on Learning Representations, 23-27 April 2026, Rio de Janeiro, Brazil
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Document
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Talk

Franzese, Giulio

Estimation of mutual information using diffusion processes

Keynote talk in Bordeaux School of Neurosciences, Frontiers in Neural Organoids Modelling, 13 April-1 May 2026, Bordeaux, France
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Report

Alberto Foresti, Mustapha Bounoua, Giulio Franzese, Luca Ambrogioni, Pietro Michiardi

Improved Sampling Schedules for Discrete Diffusion Models

Submitted to ArXiV, 6 February 2026
Detail
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Poster / Demo

Rosso, Mattia; Rossi, Simone; Franzese, Giulio; Heinonen, Markus; Filippone, Maurizio

Scaling laws for uncertainty in deep learning

EIML 2025, Epistemic Intelligence in Machine Learning, 6 December 2025, Copenhagen, Denmark
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