Thomas Gabel
Reinforcement Learning · 2009–2012
A researcher in the Science corpus: 2 papers; trusts 25 researchers and is trusted by 45 researchers here, as inferred from the citation graph.
Subfields
- Reinforcement Learning — 35 citations into it; #441 of 2,242 by trust here, #626 by citations
- Artificial Intelligence — 18 citations into it; #4,638 of 35,345 by trust here, #6,614 by citations
- Control and Systems Engineering — 11 citations into it; #2,996 of 8,257 by trust here, #1,875 by citations
- Optimization & Training — 5 citations into it
Whom Thomas Gabel trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Martin A. Riedmiller
- Dimitri P. Bertsekas
- Geoffrey J. Gordon
- Richard S. Sutton
- Andrew Barto
- Geoffrey E. Hinton
- Jan Peters
- Damien Ernst
- Michail G. Lagoudakis
- Sascha Lange
Who trusts Thomas Gabel overall
- Sascha Lange
- Sergey Levine
- Scott Fujimoto
- Romain Laroche
- Justin Fu
- Jens Kober
- Martin A. Riedmiller
- Ofir Nachum
- Aviral Kumar
- Rishabh Agarwal
Papers from Thomas Gabel's perspective
Ordered by how strongly the researchers Thomas Gabel 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
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Batch Reinforcement Learning (2012) — 699 citations
- Reinforcement learning for robot soccer (2009) — 291 citations