Lore Goetschalckx

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 103 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 21 citations into it; #8,343 of 21,575 by trust here, #8,612 by citations
• Generative Models — 12 citations into it; #794 of 1,956 by trust here, #973 by citations
• Artificial Intelligence — 6 citations into it

Whom Lore Goetschalckx trusts overall

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

1. Kaiming He
2. Bolei Zhou
3. Aditya Khosla
4. Antonio Torralba
5. Geoffrey E. Hinton
6. Alex Krizhevsky
7. Aude Oliva
8. Ross B. Girshick
9. Karen Simonyan
10. Yann LeCun

Who trusts Lore Goetschalckx overall

1. Yujun Shen
2. Yuval Alaluf
3. Patrick Esser
4. Gwanghyun Kim
5. Robin Rombach
6. Zongze Wu
7. Chenlin Meng
8. Yuri Viazovetskyi
9. Or Patashnik
10. Daniel Cohen-Or

Papers from Lore Goetschalckx's perspective

Ordered by how strongly the researchers Lore Goetschalckx 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. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• GANalyze: Toward Visual Definitions of Cognitive Image Properties (2019) — 350 citations