Nathan Dass

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 28 citations into it; #34,994 of 35,345 by trust here, #19,873 by citations
• Natural Language Processing — 26 citations into it; #5,622 of 5,688 by trust here, #3,897 by citations
• Evaluation & Benchmarks — 5 citations into it

Whom Nathan Dass trusts overall

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

1. Philipp Koehn
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Rachel Rudinger

Who trusts Nathan Dass overall

1. Emily Sheng

Papers from Nathan Dass's perspective

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

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

Their papers

• Automatically Neutralizing Subjective Bias in Text (2019) — 207 citations