:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Li, Wenqing, Feng, Xu, Jiang, Peixue, Zhu, Yinhai
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2604.13133
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Automated co-design of high-performance thermodynamic cycles via graph-based hierarchical reinforcement learning
by: Li, Wenqing
Published: (2026)

Development of low-dissipative projection method framework integrating various high-order time integration schemes using OpenFOAM
by: Guo, Hao, et al.
Published: (2023)

Flowsheet synthesis through hierarchical reinforcement learning and graph neural networks
by: Stops, Laura, et al.
Published: (2022)

Risk-anticipatory autonomous driving strategies considering vehicles' weights, based on hierarchical deep reinforcement learning
by: Chen, Di, et al.
Published: (2023)

A novel multi-agent dynamic portfolio optimization learning system based on hierarchical deep reinforcement learning
by: Sun, Ruoyu, et al.
Published: (2025)

Order-lifted data inversion/retrieval method of neighbor cells to implement general high-order schemes in unstructured-mesh-based finite-volume solution framework
by: Guo, Hao, et al.
Published: (2024)

Surgical Gym: A high-performance GPU-based platform for reinforcement learning with surgical robots
by: Schmidgall, Samuel, et al.
Published: (2023)

Emergent temporal abstractions in autoregressive models enable hierarchical reinforcement learning
by: Kobayashi, Seijin, et al.
Published: (2025)

An efficient and low-divergence method for generating inhomogeneous and anisotropic turbulence with arbitrary spectra
by: Guo, Hao, et al.
Published: (2023)

Rulebook: bringing co-routines to reinforcement learning environments
by: Fioravanti, Massimo, et al.
Published: (2025)

A hierarchical decomposition for explaining ML performance discrepancies
by: Feng, Jean, et al.
Published: (2024)

Applications of deep reinforcement learning to urban transit network design
by: Holliday, Andrew
Published: (2025)

Agentic reinforcement learning empowers next-generation chemical language models for molecular design and synthesis
by: Li, Hao, et al.
Published: (2026)

Causal prompting model-based offline reinforcement learning
by: Yu, Xuehui, et al.
Published: (2024)

Physics-Embedded Gaussian Process for Traffic State Estimation
by: Chen, Yanlin, et al.
Published: (2025)

Rank-based loss for learning hierarchical representations
by: Nolasco, Ines, et al.
Published: (2021)

Explainable reinforcement learning from human feedback to improve alignment
by: Liu, Shicheng, et al.
Published: (2025)

HDGL: A hierarchical dynamic graph representation learning model for brain disorder classification
by: Jalali, Parnian, et al.
Published: (2023)

Improving out-of-distribution generalization in graphs via hierarchical semantic environments
by: Piao, Yinhua, et al.
Published: (2024)

Leveraging LLMs for reward function design in reinforcement learning control tasks
by: Cardenoso, Franklin, et al.
Published: (2025)

CleanSurvival: Automated data preprocessing for time-to-event models using reinforcement learning
by: Koka, Yousef, et al.
Published: (2025)

Attention on flow control: transformer-based reinforcement learning for lift regulation in highly disturbed flows
by: Liu, Zhecheng, et al.
Published: (2025)

Ergodicity in reinforcement learning
by: Baumann, Dominik, et al.
Published: (2026)

Deep progressive reinforcement learning-based flexible resource scheduling framework for IRS and UAV-assisted MEC system
by: Dong, Li, et al.
Published: (2024)

Self-supervised local learning rules learn the hidden hierarchical structure of high-dimensional data
by: Delrocq, Ariane, et al.
Published: (2026)

A first realization of reinforcement learning-based closed-loop EEG-TMS
by: Humaidan, Dania, et al.
Published: (2026)

Transfer learning strategies for accelerating reinforcement-learning-based flow control
by: Salehi, Saeed
Published: (2025)

Deep learning for the design of non-Hermitian topolectrical circuits
by: Chen, Xi, et al.
Published: (2024)

Optimal scaling laws in learning hierarchical multi-index models
by: Defilippis, Leonardo, et al.
Published: (2026)

Model predictive control-based value estimation for efficient reinforcement learning
by: Wu, Qizhen, et al.
Published: (2023)

Deep reinforcement learning for irrigation scheduling using high-dimensional sensor feedback
by: Saikai, Yuji, et al.
Published: (2023)

Curriculum reinforcement learning with measurable task representation learning
by: Wen, Yongyan, et al.
Published: (2026)

RLGT: A reinforcement learning framework for extremal graph theory
by: Damnjanović, Ivan, et al.
Published: (2026)

OThink-MR1: Stimulating multimodal generalized reasoning capabilities via dynamic reinforcement learning
by: Liu, Zhiyuan, et al.
Published: (2025)

Beyond expected value: geometric mean optimization for long-term policy performance in reinforcement learning
by: Sheng, Xinyi, et al.
Published: (2025)

Chaos-based reinforcement learning with TD3
by: Matsuki, Toshitaka, et al.
Published: (2024)

Economic span selection of bridge based on deep reinforcement learning
by: Zhang, Leye, et al.
Published: (2024)

Towards Heisenberg limit without critical slowing down via quantum reinforcement learning
by: Xu, Hang, et al.
Published: (2025)

Boosting long-term forecasting performance for continuous-time dynamic graph networks via data augmentation
by: Tian, Yuxing, et al.
Published: (2023)

Pharmacophore-based design by learning on voxel grids
by: Mahmood, Omar, et al.
Published: (2025)