Peter Bhlmann

Statistics and Probability · 2011–2016

A researcher in the Science corpus: 2 papers; trusts 57 researchers and is trusted by 50 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 112 citations into it
• Artificial Intelligence — 89 citations into it; #4,120 of 35,345 by trust here, #6,266 by citations
• Computer Vision and Pattern Recognition — 50 citations into it
• Computational Mechanics — 41 citations into it
• Statistical and Nonlinear Physics — 39 citations into it
• Computational Theory and Mathematics — 38 citations into it
• Computer Networks and Communications — 27 citations into it
• Signal Processing — 24 citations into it

Whom Peter Bhlmann trusts overall

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

1. Michael W. Mahoney
2. M. J. van der Laan
3. Petros Drineas
4. Donald B. Rubin
5. Robert Tibshirani
6. Leo Breiman
7. Judea Pearl
8. Tamás Sarlós
9. Peter D. Hoff
10. James M. Robins

Who trusts Peter Bhlmann overall

1. Rajen Dinesh Shah
2. Peter Buhlmann
3. Victor Chernozhukov
4. Yaoliang Yu
5. Mohamed Hebiri
6. Veronika Rocková
7. Christopher Nowzohour
8. Alekh Agarwal
9. Yingying Fan
10. Vira Semenova

Papers from Peter Bhlmann's perspective

Ordered by how strongly the researchers Peter Bhlmann 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Et al
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Statistics for High-Dimensional Data: Methods, Theory and Applications (2011) — 1,751 citations
• Handbook of Big Data (2016) — 63 citations