:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Wolpert, David H.
Format:	Preprint
Published:	2019
Subjects:	Statistical Mechanics Machine Learning
Online Access:	https://arxiv.org/abs/1911.02700
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Strengthened second law for multi-dimensional systems coupled to multiple thermodynamic reservoirs
by: Wolpert, David H.
Published: (2020)

Stochastic thermodynamics of computation
by: Wolpert, David H.
Published: (2019)

Nonequilibrium thermodynamics of uncertain stochastic processes
by: Korbel, Jan, et al.
Published: (2022)

Machine Learning H-theorem
by: Lier, Ruben
Published: (2025)

Minimal thermodynamic cost of communication
by: Yadav, Abhishek, et al.
Published: (2024)

Weight fluctuations in (deep) linear neural networks and a derivation of the inverse-variance flatness relation
by: Gross, Markus, et al.
Published: (2023)

Entropy production bounds for systems running computer programs
by: Yadav, Abhishek, et al.
Published: (2024)

Minimal thermodynamic cost of computing with circuits
by: Yadav, Abhishek, et al.
Published: (2025)

Cross-fluctuation phase transitions reveal sampling dynamics in diffusion models
by: Ramachandran, Sai Niranjan, et al.
Published: (2025)

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

Entropy production in communication channels
by: Tasnim, Farita, et al.
Published: (2023)

Stochastic Thermodynamics of Associative Memory
by: Rooke, Spencer, et al.
Published: (2026)

SETOL: A Semi-Empirical Theory of (Deep) Learning
by: Martin, Charles H, et al.
Published: (2025)

Learned Mappings for Targeted Free Energy Perturbation between Peptide Conformations
by: Willow, Soohaeng Yoo, et al.
Published: (2023)

A family of thermodynamic uncertainty relations valid for general fluctuation theorems
by: Timpanaro, André M.
Published: (2024)

Boltzmann Bridges
by: Scharnhorst, Jordan, et al.
Published: (2024)

Disentangling Boltzmann brains, the time-asymmetry of memory, and the second law
by: Wolpert, David, et al.
Published: (2025)

Viral Load Inference in Non-Adaptive Pooled Testing
by: Sheikh, Mansoor, et al.
Published: (2024)

Work extraction with feedback control using limited resources
by: Hartle, Harrison, et al.
Published: (2024)

Uncertainty in AI-driven Monte Carlo simulations
by: Tzivrailis, Dimitrios, et al.
Published: (2025)

Thermodynamics of computations with absolute irreversibility, unidirectional transitions, and stochastic computation times
by: Manzano, Gonzalo, et al.
Published: (2023)

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

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

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

Laws of thermodynamics for exponential families
by: Balsubramani, Akshay
Published: (2025)

Improving FMQA via Initial Training Data Design Considering Marginal Bit Coverage in One-Hot Encoding
by: Hayashi, Taiga, et al.
Published: (2026)

Combining Reinforcement Learning and Tensor Networks, with an Application to Dynamical Large Deviations
by: Gillman, Edward, et al.
Published: (2022)

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

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

Posterior Collapse as Automatic Spectral Pruning
by: Hirn, Johannes
Published: (2026)

Learning the Intrinsic Dimensionality of Fermi-Pasta-Ulam-Tsingou Trajectories: A Nonlinear Approach using a Deep Autoencoder Model
by: Marchetti, Gionni
Published: (2026)

The impact of memory on learning sequence-to-sequence tasks
by: Seif, Alireza, et al.
Published: (2022)

Discovering Causal Structure with Reproducing-Kernel Hilbert Space $ε$-Machines
by: Brodu, Nicolas, et al.
Published: (2020)

$α$-divergence Improves the Entropy Production Estimation via Machine Learning
by: Kwon, Euijoon, et al.
Published: (2023)

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

A differentiable programming framework for spin models
by: Farias, Tiago de Souza, et al.
Published: (2023)

Data driven modeling for self-similar dynamics
by: Tao, Ruyi, et al.
Published: (2023)

Composing diffusion priors with explicit physical context via generative Gibbs sampling
by: Wang, Weizhou, et al.
Published: (2026)

Dynamical Regimes of Diffusion Models
by: Biroli, Giulio, et al.
Published: (2024)