Jonathan Booher
Reinforcement Learning · 2018–2019
A researcher in the Science corpus: 2 papers; trusts 33 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Reinforcement Learning — 27 citations into it
- Control and Systems Engineering — 22 citations into it
- Artificial Intelligence — 19 citations into it
- Computer Vision and Pattern Recognition — 17 citations into it
- Robotics & Control — 14 citations into it
- Mechanical Engineering — 10 citations into it
- Evaluation & Benchmarks — 7 citations into it
Whom Jonathan Booher trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jonathan Ho
- Tianhao Zhang
- Konstantinos Bousmalis
- Stefano Ermon
- Linxi (Jim) Fan
- Yuke Zhu
- Tim Salimans
- Diederik P. Kingma
- Geoffrey E. Hinton
- Pieter Abbeel
Who trusts Jonathan Booher overall
Papers from Jonathan Booher's perspective
Ordered by how strongly the researchers Jonathan Booher 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)
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge