Mathias Müller

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 3 papers; trusts 54 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 89 citations into it; #16,445 of 35,345 by trust here, #6,517 by citations
• Natural Language Processing — 79 citations into it; #2,911 of 5,688 by trust here, #1,518 by citations
• Computer Vision and Pattern Recognition — 41 citations into it; #13,581 of 21,575 by trust here, #17,757 by citations
• Evaluation & Benchmarks — 28 citations into it
• Model Architectures — 13 citations into it

Whom Mathias Müller trusts overall

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

1. Rico Sennrich
2. Geoffrey E. Hinton
3. Matt Post
4. Jimmy Ba
5. Diederik P. Kingma
6. Yoshua Bengio
7. Ilya Sutskever
8. Philipp Koehn
9. Alex Krizhevsky
10. Ashish Vaswani

Who trusts Mathias Müller overall

1. Yoav Goldberg
2. Roee Aharoni
3. Chaojun Wang
4. Rico Sennrich
5. Gongbo Tang
6. Diego Moussallem
7. Felix Stahlberg
8. Elena Voita

Papers from Mathias Müller's perspective

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

Their papers

• Findings of the 2019 Conference on Machine Translation (WMT19) (2019) — 630 citations
• Why Self-Attention? A Targeted Evaluation of Neural Machine Translation Architectures (2018) — 276 citations
• Domain Robustness in Neural Machine Translation (2019) — 104 citations