J. Trinquier

Molecular Biology · 2021

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 36 citations into it
• Computational Biology & Bioinformatics — 23 citations into it

Whom J. Trinquier trusts overall

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

1. Joe G. Greener
2. David Ruppert
3. Tunca Dogan
4. Simona Cocco
5. Tyler N. Starr
6. Matteo Figliuzzi
7. David H. Ackley
8. Olivier Rivoire
9. Jérôme Tubiana
10. Ryan R. Cheng

Papers from J. Trinquier's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Direct-coupling analysis of residue coevolution captures native contacts across many protein families
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
5. Et al
6. GENERATIVE ADVERSARIAL NETS
7. A Learning Algorithm for Boltzmann Machines
8. Long Short-Term Memory
9. ImageNet classification with deep convolutional neural networks
10. Deep Learning

Their papers

• Efficient generative modeling of protein sequences using simple autoregressive models (2021) — 95 citations