Diane Coyle

2014–2020

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Whom Diane Coyle trusts overall

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

1. Tim Miller
2. Zachary Chase Lipton

Who trusts Diane Coyle overall

1. Tim Jackson
2. P. Stoknes
3. A. Pike
4. M. Sensier
5. Martin Feldstein

Papers from Diane Coyle's perspective

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

1. The mythos of model interpretability
2. Explanation in Artificial Intelligence: Insights from the Social Sciences
3. Human-level control through deep reinforcement learning
4. ImageNet classification with deep convolutional neural networks
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Rectified Linear Units Improve Restricted Boltzmann Machines
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• GDP: A Brief but Affectionate History (2014) — 262 citations
• “Explaining” machine learning reveals policy challenges (2020) — 72 citations