Peter Meinicke

Bioinform. · 2004–2020

A researcher in the Science corpus: 6 papers; trusts 4 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Whom Peter Meinicke trusts overall

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

1. C. Burges
2. Yann LeCun
3. K. Müller
4. Yoshua Bengio

Who trusts Peter Meinicke overall

1. Eric W. Sellers
2. Dean J. Krusienski
3. Brendan Z. Allison
4. Luis F. Nicolás-Alonso
5. Non Yok

Papers from Peter Meinicke's perspective

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

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

Their papers

• BCI competition 2003-data set IIb: support vector machines for the P300 speller paradigm (2004) — 538 citations
• Orphelia: predicting genes in metagenomic sequencing reads (2009) — 143 citations
• Critical Assessment of Metagenome Interpretation – a benchmark of computational metagenomics software (2017) — 675 citations
• Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data (2015) — 1,368 citations
• Score-based prediction of genomic islands in prokaryotic genomes using hidden Markov models (2006) — 388 citations
• Tax4Fun2: prediction of habitat-specific functional profiles and functional redundancy based on 16S rRNA gene sequences (2020) — 556 citations