Matthew D. Stanley

Epidemiology · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Epidemiology — 11 citations into it
• Reinforcement Learning — 6 citations into it

Whom Matthew D. Stanley trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Keisuke Hirano
2. David Silver
3. Shamim Nemati
4. Alistair E. W. Johnson
5. Marzyeh Ghassemi
6. Volodymyr Mnih

Who trusts Matthew D. Stanley overall

1. Chao Yu

Papers from Matthew D. Stanley's perspective

Ordered by how strongly the researchers Matthew D. Stanley trusts endorse each paper. Same corpus, a different order for every researcher.

1. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
2. Policy Gradient Methods for Reinforcement Learning with Function Approximation
3. Playing Atari with Deep Reinforcement Learning (arXiv.org)
4. Deterministic Policy Gradient Algorithms
5. Reinforcement Learning: A Survey
6. MIMIC-III, a freely accessible critical care database
7. ImageNet classification with deep convolutional neural networks
8. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)
9. A data-driven approach to optimized medication dosing: a focus on heparin
10. Epidemiology of severe sepsis in the United States: Analysis of incidence, outcome, and associated costs of care (Critical Care Medicine)

Their papers

• A Deep Deterministic Policy Gradient Approach to Medication Dosing and Surveillance in the ICU (2018) — 44 citations
• An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU (2017) — 684 citations