J. Moore

Artificial Intelligence · with Hammerla · 2019

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 12 citations into it
• Safety, Robustness & Interpretability — 12 citations into it

Whom J. Moore trusts overall

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

1. Diederik P. Kingma
2. Ian J. Goodfellow
3. Christian Szegedy
4. Scott M. Lundberg
5. Alexey Kurakin
6. Avanti Shrikumar
7. Jimmy Ba
8. Nicolas Papernot
9. Geoffrey E. Hinton
10. Ilya Sutskever

Papers from J. Moore's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. ImageNet Large Scale Visual Recognition Challenge
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Explaining Deep Learning Models with Constrained Adversarial Examples (2019) — 45 citations