:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Ashworth, Cassidy, Liò, Pietro, Caso, Francesco
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Statistical Mechanics Artificial Intelligence
Online Access:	https://arxiv.org/abs/2510.16591
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Trees to Flows and Back: Unifying Decision Trees and Diffusion Models
by: Ramachandran, Sai Niranjan, et al.
Published: (2026)

Spontaneous symmetry breaking and Goldstone modes for deep information propagation
by: Iqbal, Nabil, et al.
Published: (2026)

On Distinguishing Capability Elicitation from Capability Creation in Post-Training: A Free-Energy Perspective
by: Li, Yuhao, et al.
Published: (2026)

Grokking as a Falsifiable Finite-Size Transition
by: Bi, Yuda, et al.
Published: (2026)

Thermodynamic Irreversibility of Training Algorithms
by: Ziyin, Liu, et al.
Published: (2026)

Reinforcement Learning for Microcanonical Graph Ensemble with Assortativity Constraints
by: Choi, Hoyun, et al.
Published: (2026)

Stochastic Resetting Mitigates Latent Gradient Bias of SGD from Label Noise
by: Bae, Youngkyoung, et al.
Published: (2024)

Maximum diffusion reinforcement learning
by: Berrueta, Thomas A., et al.
Published: (2023)

Spectral Architecture Search for Neural Network Models
by: Peri, Gianluca, et al.
Published: (2025)

Learning Kinetic Monte Carlo stochastic dynamics with Deep Generative Adversarial Networks
by: Lanzoni, Daniele, et al.
Published: (2025)

Entropic Confinement and Mode Connectivity in Overparameterized Neural Networks
by: Di Carlo, Luca, et al.
Published: (2025)

Statistical Mechanics and Artificial Neural Networks: Principles, Models, and Applications
by: Böttcher, Lucas, et al.
Published: (2024)

Stable Attractors for Neural networks classification via Ordinary Differential Equations (SA-nODE)
by: Marino, Raffaele, et al.
Published: (2023)

Sampling Decisions
by: Chertkov, Michael, et al.
Published: (2025)

Adaptive Path Integral Diffusion: AdaPID
by: Chertkov, Michael, et al.
Published: (2025)

Scalable Discrete Diffusion Samplers: Combinatorial Optimization and Statistical Physics
by: Sanokowski, Sebastian, et al.
Published: (2025)

IsingFormer: Augmenting Parallel Tempering With Learned Proposals
by: Bunaiyan, Saleh, et al.
Published: (2025)

Relaxation-assisted reverse annealing on nonnegative/binary matrix factorization
by: Haba, Renichiro, et al.
Published: (2025)

On the Separability of Information in Diffusion Models
by: Premkumar, Akhil
Published: (2025)

Generative Stochastic Optimal Transport: Guided Harmonic Path-Integral Diffusion
by: Chertkov, Michael
Published: (2025)

Tensor tree learns hidden relational structures in data to construct generative models
by: Harada, Kenji, et al.
Published: (2024)

Phase Transitions in the Output Distribution of Large Language Models
by: Arnold, Julian, et al.
Published: (2024)

Mixing Artificial and Natural Intelligence: From Statistical Mechanics to AI and Back to Turbulence
by: Chertkov, Michael
Published: (2024)

Temporal Memory for Resource-Constrained Agents: Continual Learning via Stochastic Compress-Add-Smooth
by: Chertkov, Michael
Published: (2026)

Entropy, concentration, and learning: a statistical mechanics primer
by: Balsubramani, Akshay
Published: (2024)

Estimating Global Input Relevance and Enforcing Sparse Representations with a Scalable Spectral Neural Network Approach
by: Chicchi, Lorenzo, et al.
Published: (2024)

Deep Neural Nets as Hamiltonians
by: Winer, Mike, et al.
Published: (2025)

Entropy-Lens: Uncovering Decision Strategies in LLMs
by: Ali, Riccardo, et al.
Published: (2025)

Performance of machine-learning-assisted Monte Carlo in sampling from simple statistical physics models
by: Del Bono, Luca Maria, et al.
Published: (2025)

Demonstrating Real Advantage of Machine-Learning-Enhanced Monte Carlo for Combinatorial Optimization
by: Del Bono, Luca Maria, et al.
Published: (2025)

Renormalized Graph Representations for Node Classification
by: Caso, Francesco, et al.
Published: (2023)

Support Vector Machine Kernels as Quantum Propagators
by: Kuo, Nan-Hong, et al.
Published: (2025)

Learning to reset in target search problems
by: Muñoz-Gil, Gorka, et al.
Published: (2025)

Breaking QAOA's Fixed Target Hamiltonian Barrier: A Fully Connected Quantum Boltzmann Machine via Bilevel Optimization
by: Liu, Jun
Published: (2026)

Privacy-preserving machine learning with tensor networks
by: Pozas-Kerstjens, Alejandro, et al.
Published: (2022)

Analytic Bridge Diffusions for Controlled Path Generation
by: Chertkov, Michael
Published: (2026)

Understanding Diffusion Models by Feynman's Path Integral
by: Hirono, Yuji, et al.
Published: (2024)

Deterministic versus stochastic dynamical classifiers: opposing random adversarial attacks with noise
by: Chicchi, Lorenzo, et al.
Published: (2024)

Effectiveness of probabilistic contact tracing in epidemic containment: the role of super-spreaders and transmission path reconstruction
by: Muntoni, A. P., et al.
Published: (2023)