Shane Storks

Natural Language Processing · 2019

A researcher in the Science corpus: 1 paper; trusts 118 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 80 citations into it
• Artificial Intelligence — 75 citations into it
• Evaluation & Benchmarks — 36 citations into it
• Computer Vision and Pattern Recognition — 31 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Shane Storks trusts overall

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

1. Geoffrey E. Hinton
2. Tomas Mikolov
3. Yoshua Bengio
4. Jason Aaron Edward Weston
5. Diederik P. Kingma
6. Peter Clark
7. Ernest Davis
8. Rachel Rudinger
9. Christopher D. Manning
10. Ilya Sutskever

Papers from Shane Storks's perspective

Ordered by how strongly the researchers Shane Storks trusts endorse each paper. Same corpus, a different order for every researcher.

1. Attention is All you Need (Neural Information Processing Systems)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet classification with deep convolutional neural networks
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. ImageNet: A large-scale hierarchical image database
8. Gradient-based learning applied to document recognition
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Commonsense Reasoning for Natural Language Understanding: A Survey of Benchmarks, Resources, and Approaches (2019) — 80 citations