Amira Abbas

Artificial Intelligence · 2020–2023

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 73 citations into it
• Computational Theory and Mathematics — 22 citations into it
• Optimization & Training — 9 citations into it
• Scaling & Learning Theory — 8 citations into it

Whom Amira Abbas trusts overall

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

1. Jorma Rissanen
2. Shun-ichi Amari
3. Peter D. Grünwald
4. Eduardo Sontag
5. Zhiwei Jia
6. Yazhen Wang
7. Behnam Neyshabur
8. Yann LeCun
9. Ryo Karakida
10. Frederik Kunstner

Who trusts Amira Abbas overall

1. M. Cerezo
2. Samson Wang

Papers from Amira Abbas's perspective

Ordered by how strongly the researchers Amira Abbas 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. Long Short-Term Memory
6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Attention is All you Need (Neural Information Processing Systems)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• The power of quantum neural networks (2020) — 1,167 citations
• Challenges and opportunities in quantum optimization (2023) — 341 citations