Hakime Öztürk

Molecular Biology · 2018

A researcher in the Science corpus: 1 paper; trusts 25 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 25 citations into it; #8,501 of 17,773 by trust here, #10,347 by citations
• Computational Theory and Mathematics — 20 citations into it; #7,323 of 12,182 by trust here, #3,562 by citations
• Artificial Intelligence — 9 citations into it
• Materials Chemistry — 9 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it
• Computational Biology & Bioinformatics — 5 citations into it
• Computational Chemistry & Drug Discovery — 5 citations into it

Whom Hakime Öztürk trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Jerome H. Friedman
4. Yann LeCun
5. L. Eon Bottou
6. Yoshua Bengio
7. Alex Krizhevsky
8. Vinod Nair
9. George E. Dahl
10. Jimmy Ba

Who trusts Hakime Öztürk overall

1. Vignesh Ram Somnath
2. Ingoo Lee
3. Jerret Ross
4. Kexin Huang
5. Rohan Gupta
6. Heba Askr
7. Raphael J. L. Townshend
8. Charlotte Bunne
9. Jongsoo Keum
10. Brian M. Belgodere

Papers from Hakime Öztürk's perspective

Ordered by how strongly the researchers Hakime Öztürk 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• DeepDTA: deep drug–target binding affinity prediction (2018) — 1,519 citations