Katie Everett

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it
• Representation & Self-Supervised Learning — 20 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Probabilistic & Bayesian Methods — 10 citations into it
• Generative Models — 7 citations into it
• Signal Processing — 6 citations into it

Whom Katie Everett trusts overall

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

1. Aapo Hyvärinen
2. Yoshua Bengio
3. Diederik P. Kingma
4. Geoffrey E. Hinton
5. Yann LeCun
6. Alex Krizhevsky
7. Xavier Glorot
8. Max Welling
9. Bernhard Schölkopf
10. Radford M. Neal

Papers from Katie Everett's perspective

Ordered by how strongly the researchers Katie Everett 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. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA (2021) — 190 citations