Richard Goodwin

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 33 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it; #23,542 of 35,345 by trust here, #25,809 by citations
• Representation & Self-Supervised Learning — 11 citations into it; #2,317 of 3,145 by trust here, #2,691 by citations
• Model Architectures — 10 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it
• Natural Language Processing — 6 citations into it; #3,955 of 5,688 by trust here, #4,682 by citations

Whom Richard Goodwin trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. R. Caruana
4. Michael I. Jordan
5. Sebastian Thrun
6. Sepp Hochreiter
7. Kyunghyun Cho
8. Alex Krizhevsky
9. J. Urgen Schmidhuber
10. Alec Go

Who trusts Richard Goodwin overall

1. Matthew Riemer

Papers from Richard Goodwin's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Representation Stability as a Regularizer for Improved Text Analytics Transfer Learning (2017) — 19 citations