Julio Martin Duarte-Carvajalino

Radiology, Nuclear Medicine and Imaging · 2009–2013

A researcher in the Science corpus: 2 papers; trusts 59 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Radiology, Nuclear Medicine and Imaging — 40 citations into it
• Computational Mechanics — 25 citations into it; #6,686 of 10,001 by trust here, #5,813 by citations
• Computer Vision and Pattern Recognition — 20 citations into it; #14,823 of 21,575 by trust here, #15,529 by citations
• Signal Processing — 13 citations into it
• Artificial Intelligence — 6 citations into it
• Biomedical Engineering — 6 citations into it; #5,707 of 10,734 by trust here, #7,661 by citations
• Media Technology — 5 citations into it

Whom Julio Martin Duarte-Carvajalino trusts overall

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

1. Michael Elad
2. E.J. Candes
3. Stéphane Mallat
4. Joel A. Tropp
5. Justin K. Romberg
6. Julien Mairal
7. Ronald A. DeVore
8. David L. Donoho
9. Rémi Gribonval
10. Scott Shaobing Chen

Who trusts Julio Martin Duarte-Carvajalino overall

1. Julien Mairal
2. Gui Zhou
3. Francis R. Bach
4. Cunhua Pan
5. Ali Mousavi
6. Lihan He
7. Jean Ponce
8. Mingyuan Zhou
9. Raja Giryes

Papers from Julio Martin Duarte-Carvajalino's perspective

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

Their papers

• Learning to Sense Sparse Signals: Simultaneous Sensing Matrix and Sparsifying Dictionary Optimization (2009) — 606 citations
• Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project (2013) — 848 citations