Dominique Fohr

Natural Language Processing · 2020

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 11 citations into it
• Artificial Intelligence — 10 citations into it

Whom Dominique Fohr trusts overall

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

1. Yoon Kim
2. Tomas Mikolov

Papers from Dominique Fohr's perspective

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

1. Efficient Estimation of Word Representations in Vector Space
2. ImageNet classification with deep convolutional neural networks
3. Attention is All you Need (Neural Information Processing Systems)
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Convolutional Neural Networks for Sentence Classification
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Long Short-Term Memory
9. Enriching Word Vectors with Subword Information
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• BERT and fastText Embeddings for Automatic Detection of Toxic Speech (2020) — 96 citations