Sarah Miller

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 27 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 50 citations into it; #33,629 of 35,345 by trust here, #21,878 by citations
• Safety, Robustness & Interpretability — 39 citations into it
• Computer Vision and Pattern Recognition — 14 citations into it
• Information Systems and Management — 11 citations into it; #3,618 of 3,842 by trust here, #2,152 by citations
• Human-Computer Interaction — 10 citations into it
• AI Ethics, Fairness & Society — 6 citations into it

Whom Sarah Miller trusts overall

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

1. Brian Y. Lim
2. Anind K. Dey
3. Finale Doshi-Velez
4. Shirley Gregor
5. Ulf Johansson
6. Daniel W. Apley
7. Been Kim
8. Riccardo Guidotti

Who trusts Sarah Miller overall

1. Q. Liao

Papers from Sarah Miller's perspective

Ordered by how strongly the researchers Sarah Miller 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. Gradient-based learning applied to document recognition
4. Explaining and Harnessing Adversarial Examples
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. Association for Computational Linguistics " Why Should I Trust You? " Explaining the Predictions of Any Classifier
8. The mythos of model interpretability
9. Long Short-Term Memory
10. Understanding Black-box Predictions via Influence Functions

Their papers

• Questioning the AI: Informing Design Practices for Explainable AI User Experiences (2020) — 990 citations