Sitan Chen

Computer Vision and Pattern Recognition · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 13 citations into it
• Generative Models — 12 citations into it
• Probabilistic & Bayesian Methods — 8 citations into it

Whom Sitan Chen trusts overall

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

1. Aapo Hyvärinen
2. Cédric Villani
3. Jean-François Le Gall
4. Yang Song
5. Santosh Srinivas Vempala
6. Tim Dockhorn
7. Diederik P. Kingma
8. Geoffrey E. Hinton
9. Arash Vahdat
10. Stefano Ermon

Who trusts Sitan Chen overall

1. Michael S. Albergo
2. Nicholas Matthew Boffi

Papers from Sitan Chen's perspective

Ordered by how strongly the researchers Sitan Chen 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. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. GENERATIVE ADVERSARIAL NETS
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions (2022) — 467 citations
• Quantum advantage in learning from experiments (2021) — 690 citations