:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Foresti, Alberto, Bounoua, Mustapha, Franzese, Giulio, Ambrogioni, Luca, Michiardi, Pietro
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2602.06849
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

MINDE: Mutual Information Neural Diffusion Estimation
by: Franzese, Giulio, et al.
Published: (2023)

Learning to Match Unpaired Data with Minimum Entropy Coupling
by: Bounoua, Mustapha, et al.
Published: (2025)

S$Ω$I: Score-based O-INFORMATION Estimation
by: Bounoua, Mustapha, et al.
Published: (2024)

INFO-SEDD: Continuous Time Markov Chains as Scalable Information Metrics Estimators
by: Foresti, Alberto, et al.
Published: (2025)

TENDE: Transfer Entropy Neural Diffusion Estimation
by: Munoz, Simon Pedro Galeano, et al.
Published: (2025)

Latent Abstractions in Generative Diffusion Models
by: Franzese, Giulio, et al.
Published: (2024)

Relative Entropy Estimation in Function Space: Theory and Applications to Trajectory Inference
by: Wang, Chao, et al.
Published: (2026)

RFMI: Estimating Mutual Information on Rectified Flow for Text-to-Image Alignment
by: Wang, Chao, et al.
Published: (2025)

Information Theoretic Text-to-Image Alignment
by: Wang, Chao, et al.
Published: (2024)

Entropic Time Schedulers for Generative Diffusion Models
by: Stancevic, Dejan, et al.
Published: (2025)

How Out-of-Equilibrium Phase Transitions can Seed Pattern Formation in Trained Diffusion Models
by: Ambrogioni, Luca
Published: (2026)

In Praise of Stubbornness: An Empirical Case for Cognitive-Dissonance Aware Continual Update of Knowledge in LLMs
by: Clemente, Simone, et al.
Published: (2025)

The Information Dynamics of Generative Diffusion
by: Stancevic, Dejan, et al.
Published: (2025)

The statistical thermodynamics of generative diffusion models: Phase transitions, symmetry breaking and critical instability
by: Ambrogioni, Luca
Published: (2023)

Stationarity without mean reversion in improper Gaussian processes
by: Ambrogioni, Luca
Published: (2023)

Measuring Semantic Information Production in Generative Diffusion Models
by: Handke, Florian, et al.
Published: (2025)

CoVAE: Consistency Training of Variational Autoencoders
by: Silvestri, Gianluigi, et al.
Published: (2025)

The Entropic Signature of Class Speciation in Diffusion Models
by: Handke, Florian, et al.
Published: (2026)

Emergence of Distortions in High-Dimensional Guided Diffusion Models
by: Ventura, Enrico, et al.
Published: (2026)

Robust and highly scalable estimation of directional couplings from time-shifted signals
by: Rouillard, Louis, et al.
Published: (2024)

Language Diffusion Models are Associative Memories Capable of Retrieving Unseen Data
by: Pham, Bao, et al.
Published: (2026)

Noise Scheduling as Information-Guided Allocation in Diffusion Training
by: Raya, Gabriel, et al.
Published: (2026)

Why Masking Diffusion Works: Condition on the Jump Schedule for Improved Discrete Diffusion
by: Amin, Alan N., et al.
Published: (2025)

Gradient-based Discrete Sampling with Automatic Cyclical Scheduling
by: Pynadath, Patrick, et al.
Published: (2024)

$\textit{Jump Your Steps}$: Optimizing Sampling Schedule of Discrete Diffusion Models
by: Park, Yong-Hyun, et al.
Published: (2024)

The Cosine Schedule is Fisher-Rao-Optimal for Masked Discrete Diffusion Models
by: Zhang, Leo, et al.
Published: (2025)

Data Augmentation for Traffic Classification
by: Wang, Chao, et al.
Published: (2024)

Manifolds, Random Matrices and Spectral Gaps: The geometric phases of generative diffusion
by: Ventura, Enrico, et al.
Published: (2024)

Memorization to Generalization: Emergence of Diffusion Models from Associative Memory
by: Pham, Bao, et al.
Published: (2025)

Digital Shielding for Cross-Domain Wi-Fi Signal Adaptation using Relativistic Average Generative Adversarial Network
by: Avola, Danilo, et al.
Published: (2025)

Scaling Laws for Uncertainty in Deep Learning
by: Rosso, Mattia, et al.
Published: (2025)

VCT: Training Consistency Models with Variational Noise Coupling
by: Silvestri, Gianluigi, et al.
Published: (2025)

Improving Antibody Design with Force-Guided Sampling in Diffusion Models
by: Kulytė, Paulina, et al.
Published: (2024)

Fine-grained Attention in Hierarchical Transformers for Tabular Time-series
by: Azorin, Raphael, et al.
Published: (2024)

An Investigation of Ear-EEG Signals for a Novel Biometric Authentication System
by: Avola, Danilo, et al.
Published: (2025)

Stratified Hazard Sampling: Minimal-Variance Event Scheduling for CTMC/DTMC Discrete Diffusion and Flow Models
by: Jang, Seunghwan, et al.
Published: (2026)

Discrete Diffusion with Sample-Efficient Estimators for Conditionals
by: Elamvazhuthi, Karthik, et al.
Published: (2026)

Improving Discrete Diffusion Models via Structured Preferential Generation
by: Rissanen, Severi, et al.
Published: (2024)

Optimizing Noise Schedules of Generative Models in High Dimensionss
by: Aranguri, Santiago, et al.
Published: (2025)

CycleBNN: Cyclic Precision Training in Binary Neural Networks
by: Fontana, Federico, et al.
Published: (2024)