:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Liu, Jinwei, Yao, Wang, Zhang, Xiao
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2504.03209
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Constraint-Preserving Neural Network Approach for Solving Mean-Field Games Equilibrium
by: Liu, Jinwei, et al.
Published: (2025)

Deep Generalized Schrödinger Bridges: From Image Generation to Solving Mean-Field Games
by: Liu, Guan-Horng, et al.
Published: (2024)

Solving PDEs With Deep Neural Nets under General Boundary Conditions
by: Zhang, Chenggong
Published: (2025)

Bounded Rationality Equilibrium Learning in Mean Field Games
by: Eich, Yannick, et al.
Published: (2024)

Adversarial Inverse Reinforcement Learning for Mean Field Games
by: Chen, Yang, et al.
Published: (2021)

High-dimensional Mean-Field Games by Particle-based Flow Matching
by: Yu, Jiajia, et al.
Published: (2025)

Solving Continuous Mean Field Games: Deep Reinforcement Learning for Non-Stationary Dynamics
by: Magnino, Lorenzo, et al.
Published: (2025)

Convergence of Actor-Critic Learning for Mean Field Games and Mean Field Control in Continuous Spaces
by: Fouque, Jean-Pierre, et al.
Published: (2025)

Equilibrium Policy Generalization: A Reinforcement Learning Framework for Cross-Graph Zero-Shot Generalization in Pursuit-Evasion Games
by: Lu, Runyu, et al.
Published: (2025)

Neural Mean-Field Games: Extending Mean-Field Game Theory with Neural Stochastic Differential Equations
by: Thöni, Anna C. M., et al.
Published: (2025)

A Mean Field Games Perspective on Evolutionary Clustering
by: Basti, Alessio, et al.
Published: (2026)

Learning in Stackelberg Mean Field Games: A Non-Asymptotic Analysis
by: Zeng, Sihan, et al.
Published: (2025)

Meta-Inverse Reinforcement Learning for Mean Field Games via Probabilistic Context Variables
by: Chen, Yang, et al.
Published: (2025)

Scalable Offline Reinforcement Learning for Mean Field Games
by: Brunnbauer, Axel, et al.
Published: (2024)

Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach
by: Fabian, Christian, et al.
Published: (2024)

Learning Surrogate Potential Mean Field Games via Gaussian Processes: A Data-Driven Approach to Ill-Posed Inverse Problems
by: Zhang, Jingguo, et al.
Published: (2025)

Learning in Mean Field Games: A Survey
by: Laurière, Mathieu, et al.
Published: (2022)

A Novel Approach to Solving Goal-Achieving Problems for Board Games
by: Shih, Chung-Chin, et al.
Published: (2021)

A Scalable Approach to Solving Simulation-Based Network Security Games
by: Lanier, Michael, et al.
Published: (2026)

Learning Mean-Field Games through Mean-Field Actor-Critic Flow
by: Zhou, Mo, et al.
Published: (2025)

Solving Diffusion ODEs with Optimal Boundary Conditions for Better Image Super-Resolution
by: Ma, Yiyang, et al.
Published: (2023)

Imbalanced Data Clustering using Equilibrium K-Means
by: He, Yudong
Published: (2024)

Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion
by: Liu, Xuantong, et al.
Published: (2024)

Paths to Equilibrium in Games
by: Yongacoglu, Bora, et al.
Published: (2024)

A Mean Curvature Approach to Boundary Detection: Geometric Insights for Unsupervised Learning
by: Levada, Alexandre L. M.
Published: (2026)

Game-Theoretic Unlearnable Example Generator
by: Liu, Shuang, et al.
Published: (2024)

Efficient and Scalable Deep Reinforcement Learning for Mean Field Control Games
by: Peng, Nianli, et al.
Published: (2024)

The Power of Regularization in Solving Extensive-Form Games
by: Liu, Mingyang, et al.
Published: (2022)

A Generalized Mean Approach for Distributed-PCA
by: Jou, Zhi-Yu, et al.
Published: (2024)

Improving Rectified Flow with Boundary Conditions
by: Hu, Xixi, et al.
Published: (2025)

Analysis of Multiscale Reinforcement Q-Learning Algorithms for Mean Field Control Games
by: Angiuli, Andrea, et al.
Published: (2024)

Generalization of Scaled Deep ResNets in the Mean-Field Regime
by: Chen, Yihang, et al.
Published: (2024)

Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models
by: Wang, Zun, et al.
Published: (2024)

Mean-Field Approximation of Cooperative Constrained Multi-Agent Reinforcement Learning (CMARL)
by: Mondal, Washim Uddin, et al.
Published: (2022)

No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes
by: Han, Minbiao, et al.
Published: (2024)

Faster Game Solving via Asymmetry of Step Sizes
by: Meng, Linjian, et al.
Published: (2025)

Simultaneously Solving Infinitely Many LQ Mean Field Games In Hilbert Spaces: The Power of Neural Operators
by: Firoozi, Dena, et al.
Published: (2025)

A Policy-Gradient Approach to Solving Imperfect-Information Games with Best-Iterate Convergence
by: Liu, Mingyang, et al.
Published: (2024)

Understanding Dynamics of Adam in Zero-Sum Games: An ODE Approach
by: Feng, Yi, et al.
Published: (2026)

A Single Online Agent Can Efficiently Learn Mean Field Games
by: Zhang, Chenyu, et al.
Published: (2024)