Abigail Graese

Computer Vision and Pattern Recognition · 2016

A researcher in the Science corpus: 1 paper; trusts 25 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 13 citations into it
• Artificial Intelligence — 12 citations into it; #28,027 of 35,345 by trust here, #29,412 by citations
• Safety, Robustness & Interpretability — 11 citations into it

Whom Abigail Graese trusts overall

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

1. Alex Krizhevsky
2. Yann LeCun
3. Christian Szegedy
4. Nicolas Papernot
5. Ian J. Goodfellow
6. Geoffrey E. Hinton
7. Jia Deng
8. Yoshua Bengio
9. Ilya Sutskever
10. Yangqing Jia

Who trusts Abigail Graese overall

1. Katja Auernhammer
2. Chuan Guo
3. Ramin Tavakoli Kolagari
4. Mayank Rana
5. Naveed Akhtar

Papers from Abigail Graese's perspective

Ordered by how strongly the researchers Abigail Graese 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. ImageNet: A large-scale hierarchical image database
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. Attention is All you Need (Neural Information Processing Systems)
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Assessing Threat of Adversarial Examples on Deep Neural Networks (2016) — 60 citations