Michael Langguth

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 33 citations into it
• Computer Vision and Pattern Recognition — 25 citations into it
• Atmospheric Science — 22 citations into it
• Global and Planetary Change — 16 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Michael Langguth trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yann LeCun
4. Alex Krizhevsky
5. Kaiming He
6. Yoshua Bengio
7. J. Urgen Schmidhuber
8. Ruslan Salakhutdinov
9. Ilya Sutskever

Papers from Michael Langguth's perspective

Ordered by how strongly the researchers Michael Langguth 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. Gradient-based learning applied to document recognition
4. Long Short-Term Memory
5. ImageNet Large Scale Visual Recognition Challenge
6. GENERATIVE ADVERSARIAL NETS
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Can deep learning beat numerical weather prediction? (2021) — 498 citations