Ryan Spring

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 56 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 53 citations into it
• Computer Vision and Pattern Recognition — 33 citations into it
• Natural Language Processing — 30 citations into it; #5,601 of 5,688 by trust here, #4,250 by citations
• Optimization & Training — 11 citations into it

Whom Ryan Spring trusts overall

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

1. Ilya Sutskever
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Yoshua Bengio
5. Alex Krizhevsky
6. Kaiming He
7. Yann LeCun
8. Jacob Devlin
9. Alex Graves
10. Ross B. Girshick

Who trusts Ryan Spring overall

1. Rohan Anil
2. Robin Jia
3. Max Bartolo
4. Vineet Gupta
5. Junnan Li
6. Dheeraj Mekala

Papers from Ryan Spring's perspective

Ordered by how strongly the researchers Ryan Spring 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. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. ImageNet Large Scale Visual Recognition Challenge
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Training Question Answering Models from Synthetic Data (2020) — 179 citations
• Compressing Gradient Optimizers via Count-Sketches (2019) — 41 citations