B. Velten

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it

Whom B. Velten trusts overall

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

1. David M. Blei
2. Tommi S. Jaakkola
3. Yoav Benjamini
4. Michael I. Jordan
5. Emma Pierson
6. Torsten Hothorn
7. Michael I. Love

Who trusts B. Velten overall

1. Malte D. Luecken
2. R. Argelaguet

Papers from B. Velten's perspective

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

1. Visualizing Data using t-SNE
2. ImageNet classification with deep convolutional neural networks
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. Controlling the false discovery rate: a practical and powerful approach to multiple testing
6. Gradient-based learning applied to document recognition
7. Learning Multiple Layers of Features from Tiny Images
8. Stochastic variational inference
9. Variational Inference: A Review for Statisticians
10. Bayesian parameter estimation via variational methods

Their papers

• Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets (2018) — 1,179 citations
• MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data (2020) — 866 citations
• Gene expression across mammalian organ development (2019) — 676 citations