Florian Buettner

Molecular Biology · 2015–2018

A researcher in the Science corpus: 7 papers; trusts 12 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 73 citations into it; #2,433 of 17,773 by trust here, #2,038 by citations
• Computer Vision and Pattern Recognition — 13 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Florian Buettner trusts overall

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

1. Oliver Stegle
2. Xiaoping Zhou
3. Johann A. Gagnon-Bartsch
4. Geoffrey E. Hinton
5. L. V. D. van der Maaten
6. Bernhard Schölkopf
7. Kazutoshi Takahashi
8. Stuart H. Orkin
9. Arjun Raj
10. Sean Bendall

Who trusts Florian Buettner overall

1. Malte D. Luecken
2. Zhicheng Ji
3. Cole Trapnell
4. Fabian J Theis
5. Andrew E. Teschendorff
6. Rhonda L. Bacher
7. F. Alexander Wolf
8. Emma Pierson
9. Tallulah S. Andrews
10. Byungjin Hwang

Papers from Florian Buettner's perspective

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

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

Their papers

• Diffusion pseudotime robustly reconstructs lineage branching (2016) — 1,334 citations
• Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells (2015) — 1,153 citations
• Diffusion maps for high-dimensional single-cell analysis of differentiation data (2015) — 665 citations
• destiny: diffusion maps for large-scale single-cell data in R (2015) — 621 citations
• Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets (2018) — 1,179 citations
• Prospective identification of hematopoietic lineage choice by deep learning (2017) — 180 citations
• Computational assignment of cell-cycle stage from single-cell transcriptome data. (2015) — 393 citations