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DIPHINE: Diffusion-based -ID Neural Estimator
Simon Pedro Galeano Munoz, Mustapha Bounoua, Giulio Franzese +2
Uncovering the true informational architecture of real-world complex systems requires disentangling how their components uniquely store, redundantly share, and synergistically inte…
Relative Entropy Estimation in Function Space: Theory and Applications to Trajectory Inference
Chao Wang, Luca Nepote, Giulio Franzese +1
Trajectory Inference (TI) seeks to recover latent dynamical processes from snapshot data, where only independent samples from time-indexed marginals are observed. In applications s…
TENDE: Transfer Entropy Neural Diffusion Estimation
Simon Pedro Galeano Munoz, Mustapha Bounoua, Giulio Franzese +2
Transfer entropy measures directed information flow in time series, and it has become a fundamental quantity in applications spanning neuroscience, finance, and complex systems ana…
Learning to Match Unpaired Data with Minimum Entropy Coupling
Mustapha Bounoua, Giulio Franzese, Pietro Michiardi
Multimodal data is a precious asset enabling a variety of downstream tasks in machine learning. However, real-world data collected across different modalities is often not paired,…
Information Theoretic Text-to-Image Alignment
Chao Wang, Giulio Franzese, Alessandro Finamore +2
Diffusion models for Text-to-Image (T2I) conditional generation have recently achieved tremendous success. Yet, aligning these models with user's intentions still involves a labori…
SI: Score-based O-INFORMATION Estimation
Mustapha Bounoua, Giulio Franzese, Pietro Michiardi
The analysis of scientific data and complex multivariate systems requires information quantities that capture relationships among multiple random variables. Recently, new informati…