Ariana J. Mann

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 19 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it
• Optimization & Training — 16 citations into it
• Computer Vision and Pattern Recognition — 12 citations into it
• Computer Networks and Communications — 9 citations into it
• Efficiency & Compression — 9 citations into it

Whom Ariana J. Mann trusts overall

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

1. Geoffrey E. Hinton
2. Yann LeCun
3. Kaiming He
4. Alex Krizhevsky
5. Yoshua Bengio
6. Angelia Nedić
7. Kamal Nigam
8. L. Eon Bottou
9. Oriol Vinyals
10. X. Zhang

Papers from Ariana J. Mann's perspective

Ordered by how strongly the researchers Ariana J. Mann 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. Learning Multiple Layers of Features from Tiny Images
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Distilling the Knowledge in a Neural Network (arXiv.org)

Their papers

• Distributed Distillation for On-Device Learning (2020) — 96 citations