Katherine Rose Driggs-Campbell

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 20 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it; #22,390 of 35,345 by trust here, #21,316 by citations
• Reinforcement Learning — 19 citations into it
• Control and Systems Engineering — 8 citations into it; #4,781 of 8,257 by trust here, #6,764 by citations

Whom Katherine Rose Driggs-Campbell trusts overall

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

1. Yarin Gal
2. Stefan Schaal
3. Craig Boutilier
4. Geoffrey E. Hinton
5. Stéphane Ross
6. John Schulman
7. Alex Krizhevsky
8. Sergey Levine
9. Nitish Srivastava
10. Diederik P. Kingma

Who trusts Katherine Rose Driggs-Campbell overall

1. Keuntaek Lee
2. Kamil Saigol
3. Stephen Tu

Papers from Katherine Rose Driggs-Campbell's perspective

Ordered by how strongly the researchers Katherine Rose Driggs-Campbell 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
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. GENERATIVE ADVERSARIAL NETS
10. Dropout: a simple way to prevent neural networks from overfitting

Their papers

• HG-DAgger: Interactive Imitation Learning with Human Experts (2018) — 372 citations
• DropoutDAgger: A Bayesian Approach to Safe Imitation Learning (2017) — 32 citations