Shamim Nemati
Artificial Intelligence · 2016–2019
A researcher in the Science corpus: 6 papers; trusts 181 researchers and is trusted by 18 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 160 citations into it; #27,873 of 35,345 by trust here, #16,166 by citations
- Reinforcement Learning — 87 citations into it; #874 of 2,242 by trust here, #1,482 by citations
- Statistics and Probability — 46 citations into it
- Epidemiology — 45 citations into it; #206 of 2,148 by trust here, #1,041 by citations
- Surgery — 39 citations into it
- Computer Vision and Pattern Recognition — 33 citations into it
- Medical & Health AI — 33 citations into it; #45 of 239 by trust here, #148 by citations
- Molecular Biology — 30 citations into it
Whom Shamim Nemati trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard S. Sutton
- Martin A. Riedmiller
- Mohammed Saeed
- Erica E. Moodie
- Geoffrey E. Hinton
- Andrew Barto
- Susan A. Murphy
- Marzyeh Ghassemi
- Volodymyr Mnih
- Andrew Y. Ng
Who trusts Shamim Nemati overall
- Chao Yu
- Pierre Humbert
- Wei Zhang
- M. M. Afsar
- Abhyuday N. Jagannatha
- Luchen Li
- Jiming Liu
- Matthieu Komorowski
- Rongmei Lin
- Aniruddh Raghu
Papers from Shamim Nemati's perspective
Ordered by how strongly the researchers Shamim Nemati trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Reinforcement Learning: An Introduction
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Reinforcement Learning in Healthcare: A Survey (2019) — 788 citations
- Optimal medication dosing from suboptimal clinical examples: A deep reinforcement learning approach (2016) — 198 citations
- Does the "Artificial Intelligence Clinician" learn optimal treatment strategies for sepsis in intensive care? (2019) — 29 citations
- 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
- Machine Learning and Decision Support in Critical Care (2016) — 408 citations