Edo Collins

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 4 papers; trusts 602 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 77 citations into it; #13,402 of 21,575 by trust here, #9,872 by citations
• Artificial Intelligence — 33 citations into it; #25,941 of 35,345 by trust here, #29,412 by citations
• Generative Models — 17 citations into it; #1,259 of 1,956 by trust here, #1,134 by citations
• Optimization & Training — 15 citations into it
• Representation & Self-Supervised Learning — 13 citations into it; #2,451 of 3,145 by trust here, #2,957 by citations
• Model Architectures — 9 citations into it
• Computer Graphics and Computer-Aided Design — 8 citations into it; #976 of 1,584 by trust here, #579 by citations
• Aerospace Engineering — 7 citations into it

Whom Edo Collins trusts overall

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

1. Kaiming He
2. Karen Simonyan
3. Alex Krizhevsky
4. Andrew Zisserman
5. Geoffrey E. Hinton
6. Diederik P. Kingma
7. Sergey Ioffe
8. Yoshua Bengio
9. Christian Szegedy
10. Yann LeCun

Who trusts Edo Collins overall

1. Weihao Xia
2. Yuval Alaluf
3. Sabine Süsstrunk
4. Justin N. M. Pinkney
5. Anpei Chen
6. Rameen Abdal
7. Or Patashnik
8. Yulun Zhang
9. Kathleen M. Lewis
10. Anton Cherepkov

Papers from Edo Collins's perspective

Ordered by how strongly the researchers Edo Collins 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
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. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Editing in Style: Uncovering the Local Semantics of GANs (2020) — 297 citations
• Deep Feature Factorization for Content-Based Image Retrieval and Localization (2019) — 9 citations
• Deep Feature Factorization For Concept Discovery (2018) — 111 citations
• Detecting Memorization in ReLU Networks (2018) — 4 citations