Saved in:
| Main Authors: | Guo, Kenny, Eckhert, Nicholas, Chhajer, Krish, Abeykoon, Luthira, Schell, Lorne |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.03666 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
CVChess: A Deep Learning Framework for Converting Chessboard Images to Forsyth-Edwards Notation
by: Abeykoon, Luthira, et al.
Published: (2025)
by: Abeykoon, Luthira, et al.
Published: (2025)
A Multiobjective Reinforcement Learning Framework for Microgrid Energy Management
by: Liu, M. Vivienne, et al.
Published: (2023)
by: Liu, M. Vivienne, et al.
Published: (2023)
Thermodynamic Liquid Manifold Networks: Physics-Bounded Deep Learning for Solar Forecasting in Autonomous Off-Grid Microgrids
by: Abdullah, Mohammed Ezzaldin Babiker
Published: (2026)
by: Abdullah, Mohammed Ezzaldin Babiker
Published: (2026)
Dynamic Context Evolution for Scalable Synthetic Data Generation
by: Lingo, Ryan, et al.
Published: (2026)
by: Lingo, Ryan, et al.
Published: (2026)
DICOM De-Identification via Hybrid AI and Rule-Based Framework for Scalable, Uncertainty-Aware Redaction
by: Naddeo, Kyle, et al.
Published: (2025)
by: Naddeo, Kyle, et al.
Published: (2025)
Federated Multi-Agent Deep Reinforcement Learning Approach via Physics-Informed Reward for Multi-Microgrid Energy Management
by: Li, Yuanzheng, et al.
Published: (2022)
by: Li, Yuanzheng, et al.
Published: (2022)
Enhancing LLM Problem Solving with REAP: Reflection, Explicit Problem Deconstruction, and Advanced Prompting
by: Lingo, Ryan, et al.
Published: (2024)
by: Lingo, Ryan, et al.
Published: (2024)
The Double Descent Behavior in Two Layer Neural Network for Binary Classification
by: Abeykoon, Chathurika S, et al.
Published: (2025)
by: Abeykoon, Chathurika S, et al.
Published: (2025)
A New Error Temporal Difference Algorithm for Deep Reinforcement Learning in Microgrid Optimization
by: Yao, Fulong, et al.
Published: (2025)
by: Yao, Fulong, et al.
Published: (2025)
A Reinforcement Learning Approach for Optimal Control in Microgrids
by: Salaorni, Davide, et al.
Published: (2025)
by: Salaorni, Davide, et al.
Published: (2025)
End-to-End Framework Integrating Generative AI and Deep Reinforcement Learning for Autonomous Ultrasound Scanning
by: Elmekki, Hanae, et al.
Published: (2025)
by: Elmekki, Hanae, et al.
Published: (2025)
Explainable AI for Radar Resource Management: Modified LIME in Deep Reinforcement Learning
by: Lu, Ziyang, et al.
Published: (2025)
by: Lu, Ziyang, et al.
Published: (2025)
Driving Privacy Forward: Mitigating Information Leakage within Smart Vehicles through Synthetic Data Generation
by: Parikh, Krish
Published: (2024)
by: Parikh, Krish
Published: (2024)
Multivariate LSTM-Based Forecasting for Renewable Energy: Enhancing Climate Change Mitigation
by: Kamrani, Farshid, et al.
Published: (2026)
by: Kamrani, Farshid, et al.
Published: (2026)
A Deep Reinforcement Learning Framework For Financial Portfolio Management
by: Li, Jinyang
Published: (2024)
by: Li, Jinyang
Published: (2024)
AutoResearch-RL: Perpetual Self-Evaluating Reinforcement Learning Agents for Autonomous Neural Architecture Discovery
by: Jain, Nilesh, et al.
Published: (2026)
by: Jain, Nilesh, et al.
Published: (2026)
Deep Reinforcement Learning for Autonomous Cyber Defence: A Survey
by: Palmer, Gregory, et al.
Published: (2023)
by: Palmer, Gregory, et al.
Published: (2023)
CarPlanner: Consistent Auto-regressive Trajectory Planning for Large-scale Reinforcement Learning in Autonomous Driving
by: Zhang, Dongkun, et al.
Published: (2025)
by: Zhang, Dongkun, et al.
Published: (2025)
Translational Gaps in Graph Transformers for Longitudinal EHR Prediction: A Critical Appraisal of GT-BEHRT
by: Tadigotla, Krish
Published: (2026)
by: Tadigotla, Krish
Published: (2026)
Diffusion-Modeled Reinforcement Learning for Carbon and Risk-Aware Microgrid Optimization
by: Zhao, Yunyi, et al.
Published: (2025)
by: Zhao, Yunyi, et al.
Published: (2025)
Optimal Learning from Label Proportions with General Loss Functions
by: Applebaum, Lorne, et al.
Published: (2025)
by: Applebaum, Lorne, et al.
Published: (2025)
Uncertainty-Aware Federated Learning for Cyber-Resilient Microgrid Energy Management
by: Babayomi, Oluleke, et al.
Published: (2025)
by: Babayomi, Oluleke, et al.
Published: (2025)
AutoSurrogate: An LLM-Driven Multi-Agent Framework for Autonomous Construction of Deep Learning Surrogate Models in Subsurface Flow
by: Liu, Jiale, et al.
Published: (2026)
by: Liu, Jiale, et al.
Published: (2026)
Integrating Reinforcement Learning and Model Predictive Control with Applications to Microgrids
by: da Silva, Caio Fabio Oliveira, et al.
Published: (2024)
by: da Silva, Caio Fabio Oliveira, et al.
Published: (2024)
Security of Deep Reinforcement Learning for Autonomous Driving: A Survey
by: Demontis, Ambra, et al.
Published: (2022)
by: Demontis, Ambra, et al.
Published: (2022)
Autonomous Navigation of Unmanned Vehicle Through Deep Reinforcement Learning
by: Xu, Letian, et al.
Published: (2024)
by: Xu, Letian, et al.
Published: (2024)
Generative AI for Deep Reinforcement Learning: Framework, Analysis, and Use Cases
by: Sun, Geng, et al.
Published: (2024)
by: Sun, Geng, et al.
Published: (2024)
Portfolio Management using Deep Reinforcement Learning
by: Pawar, Ashish Anil, et al.
Published: (2024)
by: Pawar, Ashish Anil, et al.
Published: (2024)
Enhancing Cyber Resilience of Networked Microgrids using Vertical Federated Reinforcement Learning
by: Mukherjee, Sayak, et al.
Published: (2022)
by: Mukherjee, Sayak, et al.
Published: (2022)
Action-Attentive Deep Reinforcement Learning for Autonomous Alignment of Beamlines
by: Wang, Siyu, et al.
Published: (2024)
by: Wang, Siyu, et al.
Published: (2024)
Recurrent Auto-Encoders for Enhanced Deep Reinforcement Learning in Wilderness Search and Rescue Planning
by: Ewers, Jan-Hendrik, et al.
Published: (2025)
by: Ewers, Jan-Hendrik, et al.
Published: (2025)
Auto-Agent-Distiller: Towards Efficient Deep Reinforcement Learning Agents via Neural Architecture Search
by: Fu, Yonggan, et al.
Published: (2020)
by: Fu, Yonggan, et al.
Published: (2020)
TELL-TALE: Task Efficient LLMs with Task Aware Layer Elimination
by: Naim, Omar, et al.
Published: (2025)
by: Naim, Omar, et al.
Published: (2025)
Research on Autonomous Driving Decision-making Strategies based Deep Reinforcement Learning
by: Wang, Zixiang, et al.
Published: (2024)
by: Wang, Zixiang, et al.
Published: (2024)
Autonomous Resource Management in Microservice Systems via Reinforcement Learning
by: Zou, Yujun, et al.
Published: (2025)
by: Zou, Yujun, et al.
Published: (2025)
MTS: A Deep Reinforcement Learning Portfolio Management Framework with Time-Awareness and Short-Selling
by: Gu, Fengchen, et al.
Published: (2025)
by: Gu, Fengchen, et al.
Published: (2025)
AutoBS: Autonomous Base Station Deployment with Reinforcement Learning and Digital Network Twins
by: Lee, Ju-Hyung, et al.
Published: (2025)
by: Lee, Ju-Hyung, et al.
Published: (2025)
Structure-Informed Deep Reinforcement Learning for Inventory Management
by: Maggiar, Alvaro, et al.
Published: (2025)
by: Maggiar, Alvaro, et al.
Published: (2025)
Deep Reinforcement Learning for Artificial Upwelling Energy Management
by: Zhang, Yiyuan, et al.
Published: (2023)
by: Zhang, Yiyuan, et al.
Published: (2023)
RL2Grid: Benchmarking Reinforcement Learning in Power Grid Operations
by: Marchesini, Enrico, et al.
Published: (2025)
by: Marchesini, Enrico, et al.
Published: (2025)
Similar Items
-
CVChess: A Deep Learning Framework for Converting Chessboard Images to Forsyth-Edwards Notation
by: Abeykoon, Luthira, et al.
Published: (2025) -
A Multiobjective Reinforcement Learning Framework for Microgrid Energy Management
by: Liu, M. Vivienne, et al.
Published: (2023) -
Thermodynamic Liquid Manifold Networks: Physics-Bounded Deep Learning for Solar Forecasting in Autonomous Off-Grid Microgrids
by: Abdullah, Mohammed Ezzaldin Babiker
Published: (2026) -
Dynamic Context Evolution for Scalable Synthetic Data Generation
by: Lingo, Ryan, et al.
Published: (2026) -
DICOM De-Identification via Hybrid AI and Rule-Based Framework for Scalable, Uncertainty-Aware Redaction
by: Naddeo, Kyle, et al.
Published: (2025)