Teresa Klatzer

Computer Vision and Pattern Recognition · 2015–2017

A researcher in the Science corpus: 2 papers; trusts 103 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 26 citations into it; #16,687 of 21,575 by trust here, #19,310 by citations
• Artificial Intelligence — 17 citations into it; #27,259 of 35,345 by trust here, #30,347 by citations
• Radiology, Nuclear Medicine and Imaging — 15 citations into it
• Computational Mechanics — 10 citations into it
• Optimization & Training — 10 citations into it
• Signal Processing — 7 citations into it
• Statistical Learning Theory — 6 citations into it

Whom Teresa Klatzer trusts overall

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

1. Olivier Chapelle
2. David G. Lowe
3. Christopher K. I. Williams
4. Geoffrey E. Hinton
5. Vladimir Naumovich Vapnik
6. Alex Krizhevsky
7. Andrea Vedaldi
8. Corinna Cortes
9. Francis R. Bach
10. Andrew Zisserman

Who trusts Teresa Klatzer overall

1. Stephen Gould
2. Basura Fernando
3. Florian Knoll
4. Martin Benning
5. Simon Robert Arridge
6. Claudio Gambella
7. Jinxi Xiang
8. Hemant Kumar Aggarwal

Papers from Teresa Klatzer's perspective

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

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

Their papers

• Continuous Hyper-parameter Learning for Support Vector Machines (2015) — 25 citations
• Learning a Variational Network for Reconstruction of Accelerated MRI Data (2017) — 1,801 citations