Cover Image

Reinforcement Learning for Microcanonical Graph Ensemble with Assortativity Constraints

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Choi, Hoyun, Jo, Junghyo, Lee, Deok-Sun
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Statistical Mechanics Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Perturbation Theory in a Microcanonical Ensemble
by: Pradhan, Ritapriya, et al.
Published: (2022)

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

Reinforcement Learning for Quantum Technology
by: Bukov, Marin, et al.
Published: (2026)

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)

Symmetry and Generalisation in Neural Approximations of Renormalisation Transformations
by: Ashworth, Cassidy, et al.
Published: (2025)

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

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

Neural Graph Simulator for Complex Systems
by: Choi, Hoyun, et al.
Published: (2024)

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

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

Fluctuation without dissipation: Microcanonical Langevin Monte Carlo
by: Robnik, Jakob, et al.
Published: (2023)

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

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

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)

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

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

Scalable Discrete Diffusion Samplers: Combinatorial Optimization and Statistical Physics
by: Sanokowski, Sebastian, 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)

The Constrained Origin of Canonical and Microcanonical Ensembles in Quantum Theory
by: Di Cairano, Loris
Published: (2026)

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

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

Higher-order Graph Convolutional Network with Flower-Petals Laplacians on Simplicial Complexes
by: Huang, Yiming, et al.
Published: (2023)

Microcanonical ensemble out of equilibrium
by: Belousov, Roman, et al.
Published: (2025)

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

A Rigorous Foundation for Stochastic Thermodynamics via the Microcanonical Ensemble
by: Xing, Xiangjun
Published: (2025)

Provable Reward-Agnostic Preference-Based Reinforcement Learning
by: Zhan, Wenhao, et al.
Published: (2023)

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

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

A Minimal Model of Representation Collapse: Frustration, Stop-Gradient, and Dynamics
by: Yao, Louie Hong, et al.
Published: (2026)

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

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

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

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