Frederik Kratzert

Water Science and Technology · 2019–2020

A researcher in the Science corpus: 3 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Water Science and Technology — 28 citations into it
• Environmental Engineering — 19 citations into it

Whom Frederik Kratzert trusts overall

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

1. Hoshin V. Gupta
2. Leland McInnes
3. P. Lachenbruch
4. Mohammed Alquraishi
5. Sepp Hochreiter
6. Diederik P. Kingma
7. Keith Beven
8. Qingyun Duan
9. John Healy
10. C. Prieto

Papers from Frederik Kratzert's perspective

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

1. Long Short-Term Memory
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Dropout: a simple way to prevent neural networks from overfitting
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. GENERATIVE ADVERSARIAL NETS

Their papers

• What Role Does Hydrological Science Play in the Age of Machine Learning? (2020) — 596 citations
• Toward Improved Predictions in Ungauged Basins: Exploiting the Power of Machine Learning (2019) — 684 citations
• Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets (2019) — 893 citations