Nils Strodthoff

Artificial Intelligence · Scientific Data · 2019–2022

A researcher in the Science corpus: 6 papers; trusts 130 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 54 citations into it
• Molecular Biology — 33 citations into it
• Computer Vision and Pattern Recognition — 29 citations into it
• Signal Processing — 21 citations into it
• Generative Models — 14 citations into it
• Natural Language Processing — 13 citations into it
• Model Architectures — 11 citations into it
• Management Science and Operations Research — 9 citations into it

Whom Nils Strodthoff trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Sepp Hochreiter
5. Alex Krizhevsky
6. Kaiming He
7. Ilya Sutskever
8. Yann LeCun
9. Jimmy Ba
10. Kyunghyun Cho

Who trusts Nils Strodthoff overall

1. Pedro Hermosilla
2. Hao Wu
3. Nadav Brandes
4. Hanqun Cao
5. Jonas Köhler
6. Ling Yang

Papers from Nils Strodthoff's perspective

Ordered by how strongly the researchers Nils Strodthoff 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. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• UDSMProt: universal deep sequence models for protein classification (2019) — 194 citations
• Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models (2022) — 302 citations
• Asymptotically unbiased estimation of physical observables with neural samplers. (2020) — 136 citations
• Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL (2020) — 504 citations
• PTB-XL, a large publicly available electrocardiography dataset (2020) — 1,521 citations
• Asymptotically Unbiased Generative Neural Sampling (2019) — 4 citations