Ting-Yun Chang

Computer Vision and Pattern Recognition · 2020–2022

A researcher in the Science corpus: 3 papers; trusts 314 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 75 citations into it
• Artificial Intelligence — 68 citations into it
• Natural Language Processing — 32 citations into it
• Generative Models — 22 citations into it
• Multimodal Learning — 15 citations into it
• Large Language Models — 11 citations into it
• Representation & Self-Supervised Learning — 11 citations into it
• Model Architectures — 8 citations into it

Whom Ting-Yun Chang trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Karen Simonyan
5. Alex Krizhevsky
6. Kaiming He
7. Alec Radford
8. Yann LeCun
9. Ilya Sutskever
10. Jimmy Ba

Who trusts Ting-Yun Chang overall

1. Jiacheng Liu
2. Rohit Sridhar
3. Yunzhi Yao
4. Diyi Yang
5. Axel Sauer

Papers from Ting-Yun Chang's perspective

Ordered by how strongly the researchers Ting-Yun Chang 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• TinyGAN: Distilling BigGAN for Conditional Image Generation (2020) — 27 citations
• Incorporating Commonsense Knowledge Graph in Pretrained Models for Social Commonsense Tasks (2020) — 41 citations
• CLiMB: A Continual Learning Benchmark for Vision-and-Language Tasks (2022) — 94 citations