Ryan Jiang

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 64 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 53 citations into it
• Computer Vision and Pattern Recognition — 49 citations into it
• Multimodal Learning — 30 citations into it
• Natural Language Processing — 27 citations into it
• Model Architectures — 11 citations into it
• Representation & Self-Supervised Learning — 7 citations into it

Whom Ryan Jiang trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Alex Krizhevsky
5. Diederik P. Kingma
6. Shaoqing Ren
7. Ross B. Girshick
8. Ilya Sutskever
9. Ronghang Hu
10. Karen Simonyan

Who trusts Ryan Jiang overall

1. Gary F. Marcus

Papers from Ryan Jiang's perspective

Ordered by how strongly the researchers Ryan Jiang 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality (2022) — 639 citations