Javier Zapata

Statistics and Probability · 2019

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 11 citations into it
• Artificial Intelligence — 6 citations into it
• Cognitive Neuroscience — 5 citations into it

Whom Javier Zapata trusts overall

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

1. H. Muller
2. Michael I. Jordan
3. Jane-ling Wang
4. Matthew F. Glasser
5. Fang Yao
6. Wenjing Yang
7. John A. D. Aston
8. Kehui Chen
9. Peter J. Danaher
10. Pei Wang

Papers from Javier Zapata's perspective

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

1. Gradient-based learning applied to document recognition
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. High-dimensional graphs and variable selection with the Lasso
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. Regression Shrinkage and Selection via the Lasso
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Partial Separability and Functional Graphical Models for Multivariate Gaussian Processes (2019) — 55 citations