Shoshana B. Ginsburg

Computer Vision and Pattern Recognition · 2016

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 11 citations into it
• Artificial Intelligence — 7 citations into it

Whom Shoshana B. Ginsburg trusts overall

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

1. David Ruppert
2. Sam T. Roweis
3. Ron Kohavi
4. Mikhail Belkin
5. Hanchuan Peng
6. R. Somorjai
7. Josh Tenenbaum
8. Isabelle M Guyon
9. Zheng Zhao
10. Jihun Ham

Papers from Shoshana B. Ginsburg's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Nonlinear dimensionality reduction by locally linear embedding.
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Attention is All you Need (Neural Information Processing Systems)
10. Going deeper with convolutions

Their papers

• Feature Importance in Nonlinear Embeddings (FINE): Applications in Digital Pathology (2016) — 33 citations