Hamid Reza Rabiee

Artificial Intelligence · 2017–2020

A researcher in the Science corpus: 3 papers; trusts 141 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 80 citations into it; #18,127 of 35,345 by trust here, #11,750 by citations
• Computer Vision and Pattern Recognition — 51 citations into it
• Safety, Robustness & Interpretability — 23 citations into it
• Representation & Self-Supervised Learning — 15 citations into it
• Sociology and Political Science — 14 citations into it; #18,906 of 22,756 by trust here, #12,387 by citations
• Management Science and Operations Research — 6 citations into it
• Optimization & Training — 6 citations into it
• Statistics and Probability — 5 citations into it

Whom Hamid Reza Rabiee trusts overall

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

1. Cynthia Dwork
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Karen Simonyan
5. Yann LeCun
6. Yoshua Bengio
7. Alex Krizhevsky
8. Andrew Zisserman
9. Kaiming He
10. Alexey Dosovitskiy

Who trusts Hamid Reza Rabiee overall

1. Fatemehsadat Mireshghallah

Papers from Hamid Reza Rabiee's perspective

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

Their papers

• Deep Private-Feature Extraction (2018) — 107 citations
• Multiresolution Knowledge Distillation for Anomaly Detection (2020) — 663 citations
• A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics (2017) — 266 citations