Jonathan Hayase

Artificial Intelligence · 2022–2023

A researcher in the Science corpus: 3 papers; trusts 106 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 102 citations into it
• Computer Vision and Pattern Recognition — 88 citations into it
• Optimization & Training — 28 citations into it
• Representation & Self-Supervised Learning — 15 citations into it
• Model Architectures — 13 citations into it
• Media Technology — 8 citations into it

Whom Jonathan Hayase trusts overall

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

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

Who trusts Jonathan Hayase overall

1. Yanis Labrak

Papers from Jonathan Hayase's perspective

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

Their papers

• DataComp: In search of the next generation of multimodal datasets (2023) — 734 citations
• Scalable Extraction of Training Data from (Production) Language Models (2023) — 592 citations
• Git Re-Basin: Merging Models modulo Permutation Symmetries (2022) — 518 citations