Thierry Kogej

Computational Theory and Mathematics · 2017

A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 23 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 29 citations into it; #1,994 of 12,182 by trust here, #641 by citations
• Artificial Intelligence — 24 citations into it
• Molecular Biology — 21 citations into it; #2,045 of 17,773 by trust here, #4,105 by citations
• Generative Models — 10 citations into it; #545 of 1,956 by trust here, #491 by citations
• Model Architectures — 6 citations into it
• Optimization & Training — 5 citations into it
• Spectroscopy — 5 citations into it

Whom Thierry Kogej trusts overall

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

1. Alex Graves
2. John B. O. Mitchell
3. Sepp Hochreiter
4. J. Urgen Schmidhuber
5. Tianqi Chen
6. Geoffrey E. Hinton
7. Alexandre Varnek
8. Richard S. Sutton
9. Diederik P. Kingma
10. Yoshua Bengio

Who trusts Thierry Kogej overall

1. Sergey I. Nikolenko
2. Jiaxuan You
3. Rex Ying
4. Kristina Preuer
5. Anvita Gupta
6. Marwin H. S. Segler
7. Martin Simonovsky
8. Yibo Li
9. Kenneth Atz
10. Yujia Li

Papers from Thierry Kogej's perspective

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

1. Long Short-Term Memory
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. Learning Multiple Layers of Features from Tiny Images
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Generating Sequences With Recurrent Neural Networks

Their papers

• Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks (2017) — 1,386 citations
• Generating Focussed Molecule Libraries for Drug Discovery with Recurrent Neural Networks (2017) — 98 citations