Kyle Shaffer

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 13 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 10 citations into it; #31,039 of 35,345 by trust here, #25,809 by citations
• Sociology and Political Science — 6 citations into it; #18,629 of 22,756 by trust here, #14,917 by citations
• Natural Language Processing — 5 citations into it

Whom Kyle Shaffer trusts overall

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

1. Diederik P. Kingma
2. Rie Johnson
3. Rada Mihalcea
4. Ye Zhang
5. Jeffrey Pennington
6. Victoria L. Rubin
7. James W. Pennebaker
8. Jimmy Ba
9. Song Feng
10. Andrej Karpathy

Who trusts Kyle Shaffer overall

1. Alessandro Bondielli
2. Kashyap Popat

Papers from Kyle Shaffer's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. GloVe: Global Vectors for Word Representation
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Separating Facts from Fiction: Linguistic Models to Classify Suspicious and Trusted News Posts on Twitter (2017) — 322 citations