Johannes Borgström

Artificial Intelligence · 2011–2015

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it; #33,164 of 35,345 by trust here, #24,417 by citations
• Probabilistic & Bayesian Methods — 20 citations into it; #1,470 of 1,525 by trust here, #1,136 by citations
• Statistics and Probability — 5 citations into it

Whom Johannes Borgström trusts overall

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

1. Dexter Campbell Kozen
2. Tom Minka
3. Matthew D. Hoffman
4. John M. Winn
5. Christian P. Robert
6. Avi Pfeffer
7. Daphne Koller
8. David Tolpin
9. Andrew McCallum
10. Thore Graepel

Who trusts Johannes Borgström overall

1. S. Staton
2. Timon Gehr
3. Qiang Xu
4. Sasa Misailovic
5. Todd Mytkowicz

Papers from Johannes Borgström's perspective

Ordered by how strongly the researchers Johannes Borgström 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. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A lambda-calculus foundation for universal probabilistic programming (2015) — 115 citations
• Measure Transformer Semantics for Bayesian Machine Learning (2011) — 109 citations