Nathan Dowlin

Artificial Intelligence · 2016

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 20 citations into it
• Computational Theory and Mathematics — 7 citations into it

Whom Nathan Dowlin trusts overall

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

1. Craig Gentry
2. Zvika Brakerski
3. Yann LeCun
4. Vinod Vaikuntanathan
5. Mauro Barni
6. Adriana López-Alt
7. Joppe W. Bos
8. Kristin E. Lauter
9. Shai Halevi
10. Corinna Cortes

Who trusts Nathan Dowlin overall

1. M. Sadegh Riazi
2. Fatemehsadat Mireshghallah
3. Hassan Takabi
4. Ehsan Hesamifard
5. Kim Laine
6. Nicolas Papernot
7. Florian Tramèr
8. Mohammadkazem Taram
9. Jamie Hayes
10. Bita Darvish Rouhani

Papers from Nathan Dowlin's perspective

Ordered by how strongly the researchers Nathan Dowlin trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Efficient Fully Homomorphic Encryption from (Standard) LWE
5. ON DATA BANKS AND PRIVACY HOMOMORPHISMS
6. Going deeper with convolutions
7. Learning Multiple Layers of Features from Tiny Images
8. The mnist database of handwritten digits
9. Can homomorphic encryption be practical?
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy (2016) — 1,950 citations