Luca Calatroni

Computer Vision and Pattern Recognition · 2015

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 24 citations into it; #19,997 of 21,575 by trust here, #19,310 by citations
• Computational Mechanics — 18 citations into it
• Optimization & Training — 7 citations into it
• Media Technology — 6 citations into it

Whom Luca Calatroni trusts overall

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

1. Karl Kunisch
2. Justin Domke
3. Yves Meyer
4. N. Kingsbury
5. Thomas Pock
6. Philip B. Stark
7. Richard H. Byrd
8. Julien Mairal
9. Barbara Olshausen
10. Kristian Bredies

Who trusts Luca Calatroni overall

1. Fabian Pedregosa
2. Peter Ochs
3. Matthew D. Mackay
4. René Ranftl

Papers from Luca Calatroni's perspective

Ordered by how strongly the researchers Luca Calatroni 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. ImageNet Large Scale Visual Recognition Challenge
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Bilevel approaches for learning of variational imaging models (2015) — 100 citations