Yosi Keller

Computer Vision and Pattern Recognition · 2006–2019

A researcher in the Science corpus: 3 papers; trusts 358 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 42 citations into it; #7,646 of 21,575 by trust here, #9,872 by citations
• Artificial Intelligence — 21 citations into it; #20,510 of 35,345 by trust here, #25,809 by citations
• Signal Processing — 16 citations into it; #4,224 of 7,572 by trust here, #5,086 by citations
• Generative Models — 13 citations into it
• Management Science and Operations Research — 12 citations into it
• Representation & Self-Supervised Learning — 10 citations into it
• Computational Theory and Mathematics — 8 citations into it
• Model Architectures — 7 citations into it

Whom Yosi Keller trusts overall

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

1. Alex Graves
2. Kaiming He
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Yoshua Bengio
6. Mikhail Belkin
7. Karen Simonyan
8. Diederik P. Kingma
9. Yann LeCun
10. Ilya Sutskever

Who trusts Yosi Keller overall

1. Facundo M'emoli
2. Brian Dolhansky
3. Yotam Nitzan
4. Deressa Wodajo
5. Yisroel Mirsky
6. Giorgio Patrini
7. Hasam Khalid
8. Idan Ram
9. Junke Wang
10. Renwang Chen

Papers from Yosi Keller's perspective

Ordered by how strongly the researchers Yosi Keller 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• FSGAN: Subject Agnostic Face Swapping and Reenactment (2019) — 729 citations
• Financial Time Series Prediction Using Deep Learning (2017) — 13 citations
• Data Fusion and Multicue Data Matching by Diffusion Maps (2006) — 341 citations