Benjamin Kanding

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 10 citations into it; #17,190 of 35,345 by trust here, #22,463 by citations
• Computer Vision and Pattern Recognition — 7 citations into it; #10,869 of 21,575 by trust here, #14,822 by citations

Whom Benjamin Kanding trusts overall

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

1. Diederik P. Kingma
2. James Bergstra
3. Yoshua Bengio
4. Jasper Snoek
5. Jimmy Ba
6. Olaf Ronneberger
7. Geoffrey E. Hinton
8. Emma Strubell
9. Tien-Ju Yang
10. Hugo Larochelle

Who trusts Benjamin Kanding overall

1. Aimee van Wynsberghe
2. Anne-Laure Ligozat
3. Alexandra Sasha Luccioni
4. Roberto Verdecchia
5. E. J. Husom

Papers from Benjamin Kanding's perspective

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

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

Their papers

• Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models (2020) — 433 citations