Image de couverture de livre

INFO-SEDD: Continuous Time Markov Chains as Scalable Information Metrics Estimators

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Foresti, Alberto, Franzese, Giulio, Michiardi, Pietro
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

MINDE: Mutual Information Neural Diffusion Estimation
par: Franzese, Giulio, et autres
Publié: (2023)

Improved Sampling Schedules for Discrete Diffusion Models
par: Foresti, Alberto, et autres
Publié: (2026)

S$Ω$I: Score-based O-INFORMATION Estimation
par: Bounoua, Mustapha, et autres
Publié: (2024)

Learning to Match Unpaired Data with Minimum Entropy Coupling
par: Bounoua, Mustapha, et autres
Publié: (2025)

RFMI: Estimating Mutual Information on Rectified Flow for Text-to-Image Alignment
par: Wang, Chao, et autres
Publié: (2025)

Relative Entropy Estimation in Function Space: Theory and Applications to Trajectory Inference
par: Wang, Chao, et autres
Publié: (2026)

Latent Abstractions in Generative Diffusion Models
par: Franzese, Giulio, et autres
Publié: (2024)

TENDE: Transfer Entropy Neural Diffusion Estimation
par: Munoz, Simon Pedro Galeano, et autres
Publié: (2025)

Information Theoretic Text-to-Image Alignment
par: Wang, Chao, et autres
Publié: (2024)

In Praise of Stubbornness: An Empirical Case for Cognitive-Dissonance Aware Continual Update of Knowledge in LLMs
par: Clemente, Simone, et autres
Publié: (2025)

Fine-grained Attention in Hierarchical Transformers for Tabular Time-series
par: Azorin, Raphael, et autres
Publié: (2024)

Deep Thinking by Markov Chain of Continuous Thoughts
par: Liu, Jiayu, et autres
Publié: (2025)

Markovletics: Methods and A Novel Application for Learning Continuous-Time Markov Chain Mixtures
par: Spaeh, Fabian, et autres
Publié: (2024)

Neural Continuous-Time Markov Chain: Discrete Diffusion via Decoupled Jump Timing and Direction
par: Li, Jingyuan, et autres
Publié: (2026)

Markov Chain Estimation with In-Context Learning
par: Lepage, Simon, et autres
Publié: (2025)

Scaling Laws for Uncertainty in Deep Learning
par: Rosso, Mattia, et autres
Publié: (2025)

Data Augmentation for Traffic Classification
par: Wang, Chao, et autres
Publié: (2024)

Information Geometry of Absorbing Markov-Chain and Discriminative Random Walks
par: Kimura, Masanari
Publié: (2026)

Offline Estimation of Controlled Markov Chains: Minimaxity and Sample Complexity
par: Banerjee, Imon, et autres
Publié: (2022)

Distances for Markov Chains, and Their Differentiation
par: Brugère, Tristan, et autres
Publié: (2023)

Markov Chain Variance Estimation: A Stochastic Approximation Approach
par: Agrawal, Shubhada, et autres
Publié: (2024)

Pairwise Markov Chains for Volatility Forecasting
par: Azeraf, Elie
Publié: (2024)

Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups
par: Kostic, Vladimir R., et autres
Publié: (2024)

Long Range Propagation on Continuous-Time Dynamic Graphs
par: Gravina, Alessio, et autres
Publié: (2024)

SEDD: Scalable and Efficient Dataset Deduplication with GPUs
par: Son, Youngjun, et autres
Publié: (2025)

ULTRA-MC: A Unified Approach to Learning Mixtures of Markov Chains via Hitting Times
par: Spaeh, Fabian, et autres
Publié: (2024)

Empirical PAC-Bayes Bounds for Markov Chains
par: Karagulyan, Vahe, et autres
Publié: (2025)

Coreset Markov Chain Monte Carlo
par: Chen, Naitong, et autres
Publié: (2023)

Efficient Inference for Coupled Hidden Markov Models in Continuous Time and Discrete Space
par: Migliorini, Giosue, et autres
Publié: (2025)

Scalable Deep Metric Learning on Attributed Graphs
par: Li, Xiang, et autres
Publié: (2024)

Scalable Inference-Time Annealing with Surrogate Likelihood Estimators
par: Peñaherrera, Daniel, et autres
Publié: (2026)

A Practice in Enrollment Prediction with Markov Chain Models
par: Zhao, Yan, et autres
Publié: (2024)

Stereographic Markov Chain Monte Carlo
par: Yang, Jun, et autres
Publié: (2022)

Gaussian Invariant Markov Chain Monte Carlo
par: Titsias, Michalis K., et autres
Publié: (2025)

Regret and Sample Complexity of Online Q-Learning via Concentration of Stochastic Approximation with Time-Inhomogeneous Markov Chains
par: Singh, Rahul, et autres
Publié: (2026)

An Information-Theoretic Approach to Understanding Transformers' In-Context Learning of Variable-Order Markov Chains
par: Zhou, Ruida, et autres
Publié: (2024)

Extrapolated Markov Chain Oversampling Method for Imbalanced Text Classification
par: Avela, Aleksi, et autres
Publié: (2025)

The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains
par: Edelman, Benjamin L., et autres
Publié: (2024)

Tight Analysis of Decentralized SGD: A Markov Chain Perspective
par: Versini, Lucas, et autres
Publié: (2026)

A Scalable Nonparametric Continuous-Time Survival Model through Numerical Quadrature
par: Lee, Chaeyeon, et autres
Publié: (2026)