Lauren Watson

Artificial Intelligence · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 39 citations into it
• Safety, Robustness & Interpretability — 13 citations into it
• Management Science and Operations Research — 7 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it

Whom Lauren Watson trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Yann LeCun
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Reza Shokri
7. Jia Deng
8. Matt Fredrikson
9. Milad Nasr
10. L. Eon Bottou

Who trusts Lauren Watson overall

1. Nicholas Carlini
2. Justus Mattern
3. Weijia Shi
4. Jiayuan Ye

Papers from Lauren Watson's perspective

Ordered by how strongly the researchers Lauren Watson 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. ImageNet: A large-scale hierarchical image database
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Learning Multiple Layers of Features from Tiny Images
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• On the Importance of Difficulty Calibration in Membership Inference Attacks (2021) — 197 citations
• The Shapley Value in Machine Learning (2022) — 361 citations