Cover Image

Integrating Neural Differential Forecasting with Safe Reinforcement Learning for Blood Glucose Regulation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Yushen, Zhang, Yanfu, Zhou, Xugui
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Action-Conditioned Risk Gating for Safety-Critical Control under Partial Observability
by: Liu, Yushen, et al.
Published: (2026)

Reinforcement Learning for Target Zone Blood Glucose Control
by: Mguni, David H., et al.
Published: (2025)

Safe Screening Rules for Group SLOPE
by: Bao, Runxue, et al.
Published: (2025)

Safe Screening Rules for Group OWL Models
by: Bao, Runxue, et al.
Published: (2025)

Flexible Blood Glucose Control: Offline Reinforcement Learning from Human Feedback
by: Emerson, Harry, et al.
Published: (2025)

From Prediction to Practice: A Task-Aware Evaluation Framework for Blood Glucose Forecasting
by: Namazi, Alireza, et al.
Published: (2026)

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting
by: Soumma, Shovito Barua, et al.
Published: (2026)

Stable and Safe Human-aligned Reinforcement Learning through Neural Ordinary Differential Equations
by: Zhao, Liqun, et al.
Published: (2024)

AttenGluco: Multimodal Transformer-Based Blood Glucose Forecasting on AI-READI Dataset
by: Farahmand, Ebrahim, et al.
Published: (2025)

GluMind: Multimodal Parallel Attention and Knowledge Retention for Robust Cross-Population Blood Glucose Forecasting
by: Farahmand, Ebrahim, et al.
Published: (2025)

Conditional Sequence Modeling for Safe Reinforcement Learning
by: Bai, Wensong, et al.
Published: (2026)

Verified Safe Reinforcement Learning for Neural Network Dynamic Models
by: Wu, Junlin, et al.
Published: (2024)

The Driver-Blindness Phenomenon: Why Deep Sequence Models Default to Autocorrelation in Blood Glucose Forecasting
by: Shakeri, Heman
Published: (2025)

Glycemic-Aware and Architecture-Agnostic Training Framework for Blood Glucose Forecasting in Type 1 Diabetes
by: Khamesian, Saman, et al.
Published: (2025)

Safe In-Context Reinforcement Learning
by: Moeini, Amir, et al.
Published: (2025)

Policy Bifurcation in Safe Reinforcement Learning
by: Zou, Wenjun, et al.
Published: (2024)

Blood Glucose Control Via Pre-trained Counterfactual Invertible Neural Networks
by: Jiang, Jingchi, et al.
Published: (2024)

PNAct: Crafting Backdoor Attacks in Safe Reinforcement Learning
by: Guo, Weiran, et al.
Published: (2025)

Spatiotemporal-Aware Bit-Flip Injection on DNN-based Advanced Driver Assistance Systems (extended version)
by: Zhao, Taibiao, et al.
Published: (2026)

Feasibility Consistent Representation Learning for Safe Reinforcement Learning
by: Cen, Zhepeng, et al.
Published: (2024)

Vulnerability Analysis of Safe Reinforcement Learning via Inverse Constrained Reinforcement Learning
by: Fan, Jialiang, et al.
Published: (2026)

Counterfactually Safe Reinforcement Learning
by: Li, Jingyi, et al.
Published: (2026)

Integrating LTL Constraints into PPO for Safe Reinforcement Learning
by: Zhang, Maifang, et al.
Published: (2026)

Towards Developing Safety Assurance Cases for Learning-Enabled Medical Cyber-Physical Systems
by: Bagheri, Maryam, et al.
Published: (2022)

Foundations of Safe Online Reinforcement Learning in the Linear Quadratic Regulator: $\sqrt{T}$-Regret
by: Schiffer, Benjamin, et al.
Published: (2025)

Foundations of Safe Online Reinforcement Learning in the Linear Quadratic Regulator: Generalized Baselines
by: Schiffer, Benjamin, et al.
Published: (2024)

Extreme Value Policy Optimization for Safe Reinforcement Learning
by: Gao, Shiqing, et al.
Published: (2026)

Implicit Safe Set Algorithm for Provably Safe Reinforcement Learning
by: Zhao, Weiye, et al.
Published: (2024)

Blood Glucose Level Prediction in Type 1 Diabetes Using Machine Learning
by: Chu, Soon Jynn, et al.
Published: (2025)

OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning
by: Yao, Yihang, et al.
Published: (2024)

Feasible Policy Iteration for Safe Reinforcement Learning
by: Yang, Yujie, et al.
Published: (2023)

Safe Active Learning for Gaussian Differential Equations
by: Glass, Leon, et al.
Published: (2024)

Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications
by: Liu, Puze, et al.
Published: (2024)

Safety through Permissibility: Shield Construction for Fast and Safe Reinforcement Learning
by: Politowicz, Alexander, et al.
Published: (2024)

Exchange Policy Optimization Algorithm for Semi-Infinite Safe Reinforcement Learning
by: Zhang, Jiaming, et al.
Published: (2025)

LexiSafe: Offline Safe Reinforcement Learning with Lexicographic Safety-Reward Hierarchy
by: Yang, Hsin-Jung, et al.
Published: (2026)

GUARD: A Safe Reinforcement Learning Benchmark
by: Zhao, Weiye, et al.
Published: (2023)

CIMRL: Combining IMitation and Reinforcement Learning for Safe Autonomous Driving
by: Booher, Jonathan, et al.
Published: (2024)

Safe RLHF-V: Safe Reinforcement Learning from Multi-modal Human Feedback
by: Ji, Jiaming, et al.
Published: (2025)

Skill-based Safe Reinforcement Learning with Risk Planning
by: Zhang, Hanping, et al.
Published: (2025)