Maryam Saleki

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 20 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 20 citations into it
• Probabilistic & Bayesian Methods — 12 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it
• Safety, Robustness & Interpretability — 5 citations into it

Whom Maryam Saleki trusts overall

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

1. Radford M. Neal
2. Diederik P. Kingma
3. Yann LeCun
4. Geoffrey E. Hinton
5. Max Welling
6. Yoshua Bengio
7. Alex Krizhevsky
8. Ian J. Goodfellow
9. Yarin Gal
10. Shakir Mohamed

Papers from Maryam Saleki's perspective

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

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

Their papers

• Uncertainty-Aware Deep Classifiers Using Generative Models (2020) — 90 citations