Jonathan Dodge

Artificial Intelligence · with Bellamy · 2019

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 16 citations into it
• AI Ethics, Fairness & Society — 8 citations into it

Whom Jonathan Dodge trusts overall

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

1. Toon Calders
2. Scott M. Lundberg
3. Marco Tulio Ribeiro
4. Been Kim
5. Sandra Wachter
6. John T. Cacioppo
7. Tim Brennan
8. Su-In Lee
9. Indrė Žliobaitė
10. Tim Miller

Papers from Jonathan Dodge's perspective

Ordered by how strongly the researchers Jonathan Dodge 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. ImageNet Large Scale Visual Recognition Challenge
5. ImageNet: A large-scale hierarchical image database
6. Explanation in Artificial Intelligence: Insights from the Social Sciences
7. Association for Computational Linguistics " Why Should I Trust You? " Explaining the Predictions of Any Classifier
8. Attention is All you Need (Neural Information Processing Systems)
9. Gradient-based learning applied to document recognition
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Explaining models: an empirical study of how explanations impact fairness judgment (2019) — 162 citations