Guillaume Berger

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 105 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 29 citations into it
• Artificial Intelligence — 19 citations into it
• Evaluation & Benchmarks — 9 citations into it
• Model Architectures — 6 citations into it

Whom Guillaume Berger trusts overall

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

1. Karen Simonyan
2. Kaiming He
3. Andrew Zisserman
4. Ilya Sutskever
5. Jeff Donahue
6. Geoffrey E. Hinton
7. Sergey Ioffe
8. Alex Krizhevsky
9. Ronald J. Williams
10. Ross B. Girshick

Papers from Guillaume Berger's perspective

Ordered by how strongly the researchers Guillaume Berger 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. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• ON THE EFFECTIVENESS OF TASK GRANULARITY FOR TRANSFER LEARNING (2018) — 71 citations