Clemens Meyer

Artificial Intelligence · 2018–2025

A researcher in the Science corpus: 10 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 52 citations into it
• Computer Vision and Pattern Recognition — 31 citations into it

Whom Clemens Meyer trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Kaiming He
4. Tim Salimans
5. Alex Krizhevsky
6. Danilo Jimenez Rezende
7. Yoshua Bengio
8. Max Welling
9. Yann LeCun
10. Jimmy Ba

Papers from Clemens Meyer's perspective

Ordered by how strongly the researchers Clemens Meyer 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. Attention is All you Need (Neural Information Processing Systems)
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Learning Multiple Layers of Features from Tiny Images
9. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Clinically applicable deep learning for diagnosis and referral in retinal disease (2018) — 2,402 citations
• A Probabilistic U-Net for Segmentation of Ambiguous Images (2018) — 731 citations
• Highly accurate protein structure prediction with AlphaFold (2021) — 37,531 citations
• Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context (2024) — 3,818 citations
• Highly accurate protein structure prediction for the human proteome (2021) — 2,524 citations
• Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities (2025) — 3,609 citations
• Applying and improving AlphaFold at CASP14 (2021) — 354 citations
• Developing Deep Learning Continuous Risk Models for Early Adverse Event Prediction in Electronic Health Records: an AKI Case Study (2019) — 3 citations
• A Clinically Applicable Approach to Continuous Prediction of Future Acute Kidney Injury (2019) — 949 citations
• Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy (2018) — 337 citations