Momin Abbas

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 46 citations into it
• Computer Vision and Pattern Recognition — 27 citations into it
• Optimization & Training — 12 citations into it

Whom Momin Abbas trusts overall

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

1. Chelsea Finn
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yoshua Bengio
5. Sergey Ioffe
6. Oriol Vinyals
7. Diederik P. Kingma
8. Sergey Levine
9. J. Urgen Schmidhuber
10. Ilya Sutskever

Papers from Momin Abbas's perspective

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

Their papers

• Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning (2022) — 108 citations