Mohsin Ali

Artificial Intelligence · with Bamler · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 26 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 144 citations into it
• Computer Vision and Pattern Recognition — 90 citations into it
• Probabilistic & Bayesian Methods — 52 citations into it
• Statistics and Probability — 12 citations into it

Whom Mohsin Ali trusts overall

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

1. Geoffrey E. Hinton
2. Radford M. Neal
3. Yann LeCun
4. Diederik P. Kingma
5. Alex Krizhevsky
6. Yoshua Bengio
7. Kaiming He
8. Ross B. Girshick
9. David John Cameron MacKay
10. Ilya Sutskever

Papers from Mohsin Ali's perspective

Ordered by how strongly the researchers Mohsin Ali 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A survey of uncertainty in deep neural networks (2021) — 1,852 citations
• Deep Learning Meets SAR: Concepts, models, pitfalls, and perspectives (2020) — 314 citations