Garrett Bernstein

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 36 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 29 citations into it; #31,780 of 35,345 by trust here, #33,294 by citations
• Statistics and Probability — 18 citations into it; #11,766 of 12,932 by trust here, #12,077 by citations
• Privacy & Security — 17 citations into it

Whom Garrett Bernstein trusts overall

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

1. Stephen T. Joy
2. Adam D. Smith
3. Frank McSherry
4. Cynthia Dwork
5. Trevor Park
6. Joseph Geumlek
7. Daniel Kifer
8. Yu-Xiang Wang
9. Samantha R. Cook
10. Arthur Gretton

Who trusts Garrett Bernstein overall

1. D. Sheldon
2. Satya Kuppam

Papers from Garrett Bernstein's perspective

Ordered by how strongly the researchers Garrett Bernstein 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. Learning Multiple Layers of Features from Tiny Images
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. Long Short-Term Memory
9. GENERATIVE ADVERSARIAL NETS
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Differentially Private Bayesian Inference for Exponential Families (2018) — 53 citations
• Differentially Private Bayesian Linear Regression (2019) — 66 citations