Connor Concannon

Statistics and Probability · 2017–2020

A researcher in the Science corpus: 2 papers; trusts 19 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 23 citations into it
• Safety, Robustness & Interpretability — 11 citations into it
• Artificial Intelligence — 9 citations into it
• AI Ethics, Fairness & Society — 7 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it
• Information Systems — 5 citations into it

Whom Connor Concannon trusts overall

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

1. Berk Ustun
2. Himabindu Lakkaraju
3. Jennifer L. Hill
4. Paul R. Rosenbaum
5. Cynthia Rudin
6. Donald B. Rubin
7. Gerd Gigerenzer
8. Robyn M. Dawes
9. Joseph Kang
10. Been Kim

Who trusts Connor Concannon overall

1. Alexander S. Rich
2. Menaka Narayanan

Papers from Connor Concannon's perspective

Ordered by how strongly the researchers Connor Concannon 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. Regression Shrinkage and Selection via the Lasso
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Attention is All you Need (Neural Information Processing Systems)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Simple Rules for Complex Decisions (2017) — 107 citations
• Simple rules to guide expert classifications (2020) — 44 citations