On the public citation graph
Controlling Blood Glucose For Patients With Type 1 DiabetesUsing Deep Reinforcement Learning – The Influence OfChanging The Reward Function
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-1-4615-3618-5_2openalex-snapshot
Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
inferredcites →https://doi.org/10.1007/bf00992696openalex-snapshot
Simple statistical gradient-following algorithms for connectionist reinforcement learning
inferredcites →https://doi.org/10.1016/j.asoc.2015.06.041openalex-snapshot
Controlling blood glucose variability under uncertainty using reinforcement learning and Gaussian processes
inferredcites →https://doi.org/10.1038/nature16961openalex-snapshot
Mastering the game of Go with deep neural networks and tree search
inferredcites →https://doi.org/10.1088/0967-3334/25/4/010openalex-snapshot
Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes
inferredcites →https://doi.org/10.1089/dia.2008.0138openalex-snapshot
Statistical Tools to Analyze Continuous Glucose Monitor Data
inferredcites →https://doi.org/10.1109/bhi.2018.8333436openalex-snapshot
Reinforcement-learning optimal control for type-1 diabetes
inferredcites →https://doi.org/10.1109/embc.2019.8857178openalex-snapshot
Reinforcement Learning-Based Adaptive Insulin Advisor for Individuals with Type 1 Diabetes Patients under Multiple Daily Injections Therapy
inferredcites →https://doi.org/10.1109/mlsp.2018.8516946openalex-snapshot
CONTROLLING BLOOD GLUCOSE LEVELS IN PATIENTS WITH TYPE 1 DIABETES USING FITTED Q-ITERATIONS AND FUNCTIONAL FEATURES
inferredcites →https://doi.org/10.1177/193229681000400117openalex-snapshot
Simulation Environment to Evaluate Closed-Loop Insulin Delivery Systems in Type 1 Diabetes
inferredcites →https://doi.org/10.4230/oasics.dx.2024.16openalex-snapshot
Diagnosing Non-Intermittent Anomalies in Reinforcement Learning Policy Executions (Short Paper)
inferredcites →https://doi.org/10.48550/arxiv.1502.05477openalex-snapshot
Trust Region Policy Optimization
inferredcites →https://doi.org/10.48550/arxiv.1604.06778openalex-snapshot
Benchmarking Deep Reinforcement Learning for Continuous Control
inferredcites →https://doi.org/10.48550/arxiv.1901.09330openalex-snapshot
Reward Shaping via Meta-Learning
inferredcites →https://doi.org/10.5281/zenodo.1060214openalex-snapshot
Agent-Based Simulation For Blood Glucose Control In Diabetic Patients
What points at this work
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inferred← citeshttps://doi.org/10.2139/ssrn.4647947openalex-extracted
Partially Observable Reinforcement Learning for Blood Glucose Control Under Missing Data
inferred← citeshttps://doi.org/10.1016/j.jbi.2023.104376openalex-snapshot
Offline reinforcement learning for safer blood glucose control in people with type 1 diabetes
inferred← citeshttps://doi.org/10.3390/app10228037openalex-snapshot
Risk-Averse Food Recommendation Using Bayesian Feedforward Neural Networks for Patients with Type 1 Diabetes Doing Physical Activities
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