Sarah Schulz

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 8 citations into it; #11,174 of 21,575 by trust here, #10,154 by citations

Whom Sarah Schulz trusts overall

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

1. Li Fei-Fei

Who trusts Sarah Schulz overall

1. Giulia Vilone
2. Nadia Burkart
3. Andreas Holzinger
4. Gabrielle Ras
5. Adrien Bennetot
6. Longo Luca
7. Bertie Vidgen

Papers from Sarah Schulz's perspective

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

1. Deep Visual-Semantic Alignments for Generating Image Descriptions
2. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Image Captioning with Semantic Attention
7. DenseCap: Fully Convolutional Localization Networks for Dense Captioning
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. The mythos of model interpretability

Their papers

• What Does Explainable AI Really Mean? A New Conceptualization of Perspectives (2017) — 483 citations