Andreas Hug

Natural Language Processing · 2018

A researcher in the Science corpus: 1 paper; trusts 57 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 39 citations into it
• Artificial Intelligence — 37 citations into it
• Representation & Self-Supervised Learning — 25 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it
• Evaluation & Benchmarks — 8 citations into it

Whom Andreas Hug trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Omer Levy
4. Eneko Agirre
5. Ilya Sutskever
6. Tomas Mikolov
7. Diederik P. Kingma
8. Yann LeCun
9. Alex Krizhevsky
10. Christopher D. Manning

Papers from Andreas Hug's perspective

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

1. ImageNet classification with deep convolutional neural networks
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. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Context Mover's Distance & Barycenters: Optimal transport of contexts for building representations (2018) — 27 citations