Julian Wyatt

Computer Vision and Pattern Recognition · 2022

A researcher in the Science corpus: 1 paper; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 13 citations into it
• Artificial Intelligence — 10 citations into it
• Generative Models — 8 citations into it

Whom Julian Wyatt trusts overall

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

1. Ken Perlin
2. Prafulla Dhariwal
3. Thomas Schlegl
4. Individualized Treat
5. Aäron van den Oord
6. Diederik P. Kingma
7. Sergey Zagoruyko
8. Tim Salimans
9. Geoffrey E. Hinton
10. Jonathan Ho

Who trusts Julian Wyatt overall

1. Amirhossein Kazerouni
2. Zhaopeng Gu
3. Tran Dinh Tien
4. Ling Yang

Papers from Julian Wyatt's perspective

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

Their papers

• AnoDDPM: Anomaly Detection with Denoising Diffusion Probabilistic Models using Simplex Noise (2022) — 484 citations