Copertina

Laws of thermodynamics for exponential families

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Balsubramani, Akshay
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Statistical Mechanics Machine Learning Statistics Theory
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Entropy, concentration, and learning: a statistical mechanics primer
di: Balsubramani, Akshay
Pubblicazione: (2024)

Statistics of Min-max Normalized Eigenvalues in Random Matrices
di: Nakada, Hyakka, et al.
Pubblicazione: (2025)

Susceptibilities and Patterning: A Primer on Linear Response in Bayesian Learning
di: Elliott, Chris, et al.
Pubblicazione: (2026)

Review and Prospect of Algebraic Research in Equivalent Framework between Statistical Mechanics and Machine Learning Theory
di: Watanabe, Sumio
Pubblicazione: (2024)

Information-Geometric Decomposition of Generalization Error in Unsupervised Learning
di: Kim, Gilhan
Pubblicazione: (2026)

Sliding down the stairs: how correlated latent variables accelerate learning with neural networks
di: Bardone, Lorenzo, et al.
Pubblicazione: (2024)

A renormalization-group inspired lattice-based framework for piecewise generalized linear models
di: Chang, Joshua C.
Pubblicazione: (2026)

Training thermodynamic computers by gradient descent
di: Whitelam, Stephen
Pubblicazione: (2025)

An Optimized Franz-Parisi Criterion and its Equivalence with SQ Lower Bounds
di: Chen, Siyu, et al.
Pubblicazione: (2025)

The monotonicity of the Franz-Parisi potential is equivalent with Low-degree MMSE lower bounds
di: Tsirkas, Konstantinos, et al.
Pubblicazione: (2026)

Speed-accuracy relations for diffusion models: Wisdom from nonequilibrium thermodynamics and optimal transport
di: Ikeda, Kotaro, et al.
Pubblicazione: (2024)

Pointwise Generalization in Deep Neural Networks
di: Li, Shaojie, et al.
Pubblicazione: (2026)

Growth-Optimal E-Variables and an extension to the multivariate Csiszár-Sanov-Chernoff Theorem
di: Grünwald, Peter, et al.
Pubblicazione: (2024)

Coupled Entropy: A Goldilocks Generalization for Complex Systems
di: Nelson, Kenric P.
Pubblicazione: (2025)

A new pathway to generative artificial intelligence by minimizing the maximum entropy
di: Miotto, Mattia, et al.
Pubblicazione: (2025)

Neural Entropy
di: Premkumar, Akhil
Pubblicazione: (2024)

The Thermodynamic Costs of Simple Linear Regression
di: D'Ambrosia, Samuel H., et al.
Pubblicazione: (2026)

Learning to erase quantum states: thermodynamic implications of quantum learning theory
di: Zhao, Haimeng, et al.
Pubblicazione: (2025)

Way More Than the Sum of Their Parts: From Statistical to Structural Mixtures
di: Crutchfield, James P.
Pubblicazione: (2025)

A theoretical perspective on mode collapse in variational inference
di: Soletskyi, Roman, et al.
Pubblicazione: (2024)

Data efficiency, dimensionality reduction, and the generalized symmetric information bottleneck
di: Martini, K. Michael, et al.
Pubblicazione: (2023)

Deep Variational Multivariate Information Bottleneck -- A Framework for Variational Losses
di: Abdelaleem, Eslam, et al.
Pubblicazione: (2023)

The Role of Pseudo-labels in Self-training Linear Classifiers on High-dimensional Gaussian Mixture Data
di: Takahashi, Takashi
Pubblicazione: (2022)

Deriving Lehmer and Hölder means as maximum weighted likelihood estimates for the multivariate exponential family
di: Ziou, Djemel, et al.
Pubblicazione: (2024)

Nonlinear thermodynamic computing out of equilibrium
di: Whitelam, Stephen, et al.
Pubblicazione: (2024)

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics
di: Ghosh, Subhroshekhar, et al.
Pubblicazione: (2026)

Polyformer: a generative framework for thermodynamic modeling of polymeric molecules
di: Valentini, Alessio, et al.
Pubblicazione: (2026)

Beyond the Power Law: Estimation, Goodness-of-Fit, and a Semiparametric Extension in Complex Networks
di: Jerez-Lillo, Nixon, et al.
Pubblicazione: (2023)

Universal behaviors of the multi-time correlation functions of random processes with renewal: the step noise case (the random velocity of a Lévy walk)
di: Bianucci, Marco, et al.
Pubblicazione: (2025)

Hessian Geometry of Latent Space in Generative Models
di: Lobashev, Alexander, et al.
Pubblicazione: (2025)

Compression, Regularity, Randomness and Emergent Structure: Rethinking Physical Complexity in the Data-Driven Era
di: Dehghani, Nima
Pubblicazione: (2025)

Tsallis Entropy derived from the Chaitin-Kolmogorov Informational Entropy
di: Deppman, Airton
Pubblicazione: (2026)

Generalized free energy and excess/housekeeping decomposition in nonequilibrium systems: from large deviations to thermodynamic speed limits
di: Kolchinsky, Artemy, et al.
Pubblicazione: (2024)

Scalable Boltzmann Generators for equilibrium sampling of large-scale materials
di: Schebek, Maximilian, et al.
Pubblicazione: (2025)

Emergence of Nonequilibrium Latent Cycles in Unsupervised Generative Modeling
di: Baiesi, Marco, et al.
Pubblicazione: (2025)

Machine Learning H-theorem
di: Lier, Ruben
Pubblicazione: (2025)

Landscape Complexity for the Empirical Risk of Generalized Linear Models: Discrimination between Structured Data
di: Tsironis, Theodoros G., et al.
Pubblicazione: (2025)

Dynamical symmetries in the fluctuation-driven regime: an application of Noether's theorem to noisy dynamical systems
di: Vastola, John J.
Pubblicazione: (2025)

Optimised Feature Subset Selection via Simulated Annealing
di: Martínez-García, Fernando, et al.
Pubblicazione: (2025)

Plastic tensor networks for interpretable generative modeling
di: Akamatsu, Katsuya O., et al.
Pubblicazione: (2025)