Samuel Barrett
Artificial Intelligence · 2010–2022
A researcher in the Science corpus: 5 papers; trusts 17 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 38 citations into it
- Reinforcement Learning — 35 citations into it; #1,683 of 2,242 by trust here, #1,864 by citations
- Management Science and Operations Research — 15 citations into it
- Biomedical Engineering — 6 citations into it
- Computer Vision and Pattern Recognition — 5 citations into it
Whom Samuel Barrett trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Peter Stone
- Matthew E. Taylor
- Richard S. Sutton
- James S. Albus
- Andrew Barto
- Gavin Adrian Rummery
- Satinder Singh
- Sylvain Gelly
- Levente Kocsis
- Todd Hester
Who trusts Samuel Barrett overall
- Stefano V. Albrecht
- Owen Macindoe
- Arrasy Rahman
- Peter Stone
- Chelsea Finn
- Bruno Castro da Silva
- Niklas Höpner
- Filippos Christianos
- Tianhe Yu
- Ignasi Clavera Gilaberte
Papers from Samuel Barrett's perspective
Ordered by how strongly the researchers Samuel Barrett trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Reinforcement Learning: An Introduction
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Making friends on the fly: Cooperating with new teammates (2017) — 141 citations
- Outracing champion Gran Turismo drivers with deep reinforcement learning (2022) — 497 citations
- Humanoid robots learning to walk faster: from the real world to simulation and back (2013) — 97 citations
- Empirical evaluation of ad hoc teamwork in the pursuit domain (2011) — 159 citations
- Transfer learning for reinforcement learning on a physical robot (2010) — 80 citations