Jack Turner

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 242 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 93 citations into it
• Computer Vision and Pattern Recognition — 89 citations into it
• Model Architectures — 29 citations into it
• Efficiency & Compression — 26 citations into it
• Representation & Self-Supervised Learning — 16 citations into it
• Optimization & Training — 14 citations into it
• Evaluation & Benchmarks — 12 citations into it
• Neural Architecture Search & AutoML — 11 citations into it

Whom Jack Turner trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Yoshua Bengio
5. Diederik P. Kingma
6. Yann LeCun
7. Ruslan Salakhutdinov
8. Ilya Sutskever
9. Karen Simonyan
10. J. Urgen Schmidhuber

Who trusts Jack Turner overall

1. Steinar Laenen
2. Jake Snell
3. Wuyang Chen
4. Mohamed S. Abdelfattah

Papers from Jack Turner's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
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

• Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels (2020) — 163 citations
• Neural Architecture Search without Training (2020) — 496 citations
• Pruning neural networks: is it time to nip it in the bud? (2018) — 31 citations