Markus Müller

Artificial Intelligence · with Niehues · 2018–2019

A researcher in the Science corpus: 3 papers; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 50 citations into it
• Natural Language Processing — 25 citations into it
• Optimization & Training — 7 citations into it

Whom Markus Müller trusts overall

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

1. Alex Graves
2. Geoffrey E. Hinton
3. Christian Szegedy
4. Yoshua Bengio
5. Yarin Gal
6. Diederik P. Kingma
7. Dzmitry Bahdanau
8. Alex Krizhevsky
9. Ilya Sutskever
10. Yann LeCun

Papers from Markus Müller's perspective

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

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

Their papers

• Very Deep Self-Attention Networks for End-to-End Speech Recognition (2019) — 172 citations
• Linguistic Unit Discovery from Multi-Modal Inputs in Unwritten Languages: Summary of the “Speaking Rosetta” JSALT 2017 Workshop (2018) — 34 citations
• Open Source Toolkit for Speech to Text Translation (2018) — 14 citations