Jonas Guan

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it
• Representation & Self-Supervised Learning — 11 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it
• Safety, Robustness & Interpretability — 9 citations into it

Whom Jonas Guan trusts overall

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

1. Nicolas Papernot
2. Geoffrey E. Hinton
3. Kaiming He
4. Tribhuvanesh Orekondy
5. Alex Krizhevsky
6. Pratyush Maini

Papers from Jonas Guan's perspective

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

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

Their papers

• On the Difficulty of Defending Self-Supervised Learning against Model Extraction (2022) — 36 citations