Kevin Vervier

Molecular Biology · 2015–2019

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 48 citations into it
• Ecology — 17 citations into it

Whom Kevin Vervier trusts overall

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

1. L. Eon Bottou
2. Genome analysis
3. Derrick E. Wood
4. David Koslicki
5. Heng Li
6. Alekh Agarwal
7. Qiong Wang
8. Sören Sonnenburg
9. Alice Carolyn McHardy
10. Steven L. Salzberg

Papers from Kevin Vervier's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Stunted microbiota and opportunistic pathogen colonisation in caesarean section birth (2019) — 893 citations
• Large-scale machine learning for metagenomics sequence classification (2015) — 82 citations