Piotr Zielenkiewicz

Computational Theory and Mathematics · 2010–2017

A researcher in the Science corpus: 2 papers; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 26 citations into it
• Molecular Biology — 25 citations into it
• Materials Chemistry — 18 citations into it
• Computational Chemistry & Drug Discovery — 15 citations into it
• Computational Biology & Bioinformatics — 7 citations into it

Whom Piotr Zielenkiewicz trusts overall

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

1. Steven Henikoff
2. Pedro J. Ballester
3. Jacob D. Durrant
4. Marcel L. Verdonk
5. George E. Dahl
6. Alessandro Lusci
7. Michael K. K. Leung
8. Christof Angermueller
9. Steven M. Kearnes
10. Matthew Ragoza

Papers from Piotr Zielenkiewicz's perspective

Ordered by how strongly the researchers Piotr Zielenkiewicz 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. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. Going deeper with convolutions
9. Learning Multiple Layers of Features from Tiny Images
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Development and evaluation of a deep learning model for protein–ligand binding affinity prediction (2017) — 530 citations
• Why similar protein sequences encode similar three-dimensional structures? (2010) — 103 citations