Hui-Tang Chang

Computer Vision and Pattern Recognition · 2022

A researcher in the Science corpus: 1 paper; trusts 36 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 57 citations into it
• Generative Models — 45 citations into it
• Statistical and Nonlinear Physics — 8 citations into it

Whom Hui-Tang Chang trusts overall

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

1. Diederik P. Kingma
2. Jonathan Ho
3. Geoffrey E. Hinton
4. Yuval Alaluf
5. Alex Krizhevsky
6. Yoshua Bengio

Papers from Hui-Tang Chang's perspective

Ordered by how strongly the researchers Hui-Tang Chang trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• Imagic: Text-Based Real Image Editing with Diffusion Models (2022) — 1,531 citations