Zahra Kadkhodaie

Computer Vision and Pattern Recognition · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 297 researchers and is trusted by 29 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 56 citations into it; #8,132 of 21,575 by trust here, #15,529 by citations
• Computational Mechanics — 23 citations into it; #3,066 of 10,001 by trust here, #5,813 by citations
• Probabilistic & Bayesian Methods — 19 citations into it
• Generative Models — 18 citations into it; #773 of 1,956 by trust here, #1,681 by citations
• Media Technology — 17 citations into it
• Artificial Intelligence — 13 citations into it
• Optimization & Training — 6 citations into it

Whom Zahra Kadkhodaie trusts overall

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

1. Aapo Hyvärinen
2. Yoshua Bengio
3. Diederik P. Kingma
4. Pascal Vincent
5. Yang Song
6. Geoffrey E. Hinton
7. David L. Donoho
8. Jian Zhang
9. Alex Krizhevsky
10. Dmitry Ulyanov

Who trusts Zahra Kadkhodaie overall

1. Hyungjin Chung
2. Alexia Jolicoeur-Martineau
3. Yang Song
4. Chitwan Saharia
5. Jay Whang
6. Florinel-Alin Croitoru
7. Y. Tashiro
8. Alexandros Graikos
9. Stefano Ermon
10. William Harvey

Papers from Zahra Kadkhodaie's perspective

Ordered by how strongly the researchers Zahra Kadkhodaie 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. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Solving Linear Inverse Problems Using the Prior Implicit in a Denoiser (2020) — 106 citations
• Stochastic Solutions for Linear Inverse Problems using the Prior Implicit in a Denoiser (2021) — 193 citations