Jonathan Schwan

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 74 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 51 citations into it
• Computer Vision and Pattern Recognition — 46 citations into it
• Meta & Continual Learning — 18 citations into it

Whom Jonathan Schwan trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Alex Krizhevsky
4. Yoshua Bengio
5. Diederik P. Kingma
6. Ross B. Girshick
7. Yann LeCun
8. Ilya Sutskever
9. Karen Simonyan
10. Andrew Zisserman

Papers from Jonathan Schwan's perspective

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

Their papers

• Self-Supervised Features Improve Open-World Learning (2021) — 15 citations