J. Jiménez

Computational Theory and Mathematics · with Fabritiis · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 10 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 26 citations into it; #7,759 of 12,182 by trust here, #1,184 by citations
• Molecular Biology — 25 citations into it; #14,073 of 17,773 by trust here, #6,746 by citations
• Materials Chemistry — 20 citations into it; #5,617 of 11,513 by trust here, #6,536 by citations
• Artificial Intelligence — 18 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Computational Chemistry & Drug Discovery — 13 citations into it; #341 of 425 by trust here, #247 by citations

Whom J. Jiménez trusts overall

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

1. Diederik P. Kingma
2. Karen Simonyan
3. Marwin H. S. Segler
4. Dorin Comaniciu
5. Alexander S. Rose
6. Jimmy Ba
7. Sepp Hochreiter
8. Yoshua Bengio
9. Geoffrey E. Hinton
10. Andrew Zisserman

Who trusts J. Jiménez overall

1. Anastasiia V. Sadybekov
2. Tomohide Masuda
3. Kevin Kaichuang Yang
4. Vignesh Ram Somnath
5. Bian Li
6. Raphael J. L. Townshend
7. Shaun M. Kandathil
8. Marta M. Stepniewska-Dziubinska
9. Pedro H. M. Torres
10. Mostafa Karimi

Papers from J. Jiménez's perspective

Ordered by how strongly the researchers J. Jiménez trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Long Short-Term Memory
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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• DeepSite: protein‐binding site predictor using 3D‐convolutional neural networks (2017) — 650 citations
• KDEEP: Protein-Ligand Absolute Binding Affinity Prediction via 3D-Convolutional Neural Networks (2018) — 726 citations
• Shape-Based Generative Modeling for de Novo Drug Design (2019) — 208 citations