Philipp Renz

Computational Theory and Mathematics · 2018–2022

A researcher in the Science corpus: 4 papers; trusts 27 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 50 citations into it
• Materials Chemistry — 48 citations into it
• Computational Chemistry & Drug Discovery — 41 citations into it
• Artificial Intelligence — 39 citations into it
• Computer Vision and Pattern Recognition — 29 citations into it
• Molecular Biology — 28 citations into it
• Model Architectures — 21 citations into it
• Generative Models — 18 citations into it

Whom Philipp Renz trusts overall

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

1. Sepp Hochreiter
2. Marwin H. S. Segler
3. Geoffrey E. Hinton
4. Daniel M. Lowe
5. Kaiming He
6. Yoshua Bengio
7. J. Urgen Schmidhuber
8. David Weininger
9. Günter Klambauer
10. Alex Krizhevsky

Who trusts Philipp Renz overall

1. Dan Friedman
2. Jaehyeong Jo
3. José Jiménez-Luna

Papers from Philipp Renz's perspective

Ordered by how strongly the researchers Philipp Renz 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. Long Short-Term Memory
4. Attention is All you Need (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery (2018) — 454 citations
• Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield Networks (2022) — 90 citations
• Modern Hopfield Networks for Few- and Zero-Shot Reaction Prediction (2021) — 10 citations
• Fréchet ChemblNet Distance: A metric for generative models for molecules (2018) — 14 citations