Lotta Maria Ellingsen

Computer Vision and Pattern Recognition · 2019

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

Subfields

• Computer Vision and Pattern Recognition — 11 citations into it
• Optimization & Training — 11 citations into it
• Artificial Intelligence — 9 citations into it
• Radiology, Nuclear Medicine and Imaging — 6 citations into it

Whom Lotta Maria Ellingsen trusts overall

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

1. John Ashburner
2. Sergey Ioffe
3. Robert Tibshirani

Papers from Lotta Maria Ellingsen's perspective

Ordered by how strongly the researchers Lotta Maria Ellingsen 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. Gradient-based learning applied to document recognition
3. Regression Shrinkage and Selection via the Lasso
4. Scikit-learn: Machine Learning in Python
5. Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)
6. ImageNet classification with deep convolutional neural networks
7. Deep Learning
8. Addendum: Regularization and variable selection via the elastic net
9. Ridge Regression: Biased Estimation for Nonorthogonal Problems
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• Brain age prediction using deep learning uncovers associated sequence variants (2019) — 361 citations