Alex J. Cannon

Global and Planetary Change · 2002–2017

A researcher in the Science corpus: 5 papers; trusts 43 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Global and Planetary Change — 28 citations into it; #929 of 10,225 by trust here, #4,099 by citations
• Atmospheric Science — 23 citations into it; #442 of 4,804 by trust here, #1,705 by citations
• Statistics and Probability — 10 citations into it
• Environmental Engineering — 5 citations into it; #894 of 5,479 by trust here, #2,867 by citations
• Finance — 5 citations into it

Whom Alex J. Cannon trusts overall

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

1. Roger W. Koenker
2. Leo Breiman
3. Petra Friederichs
4. Michael A. Stephens
5. Francesco Mezzadri
6. Colin Chen
7. François Pitié
8. Mathieu Vrac
9. Lin Wang
10. A. Imbert

Who trusts Alex J. Cannon overall

1. S. Lange
2. Christoph Bergmeir
3. Chao Li
4. Jakob Zscheischler
5. Jan Gasthaus
6. José Manuel Benítez
7. Vijay P. Singh
8. Erich Fischer
9. M. Grillakis
10. M. Holthuijzen

Papers from Alex J. Cannon's perspective

Ordered by how strongly the researchers Alex J. Cannon 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. Multitask Learning
4. Regression Shrinkage and Selection via the Lasso
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. Bagging Predictors

Their papers

• Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables (2017) — 570 citations
• Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes? (2015) — 1,332 citations
• Quantile regression neural networks: Implementation in R and application to precipitation downscaling (2011) — 390 citations
• Probabilistic Multisite Precipitation Downscaling by an Expanded Bernoulli–Gamma Density Network (2008) — 123 citations
• Synoptic Map-Pattern Classification Using Recursive Partitioning and Principal Component Analysis (2002) — 69 citations