Parham Aarabi

Computer Vision and Pattern Recognition · 2018–2021

A researcher in the Science corpus: 2 papers; trusts 386 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 46 citations into it
• Generative Models — 23 citations into it
• Artificial Intelligence — 22 citations into it
• Safety, Robustness & Interpretability — 11 citations into it
• Signal Processing — 5 citations into it

Whom Parham Aarabi trusts overall

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

1. Ross B. Girshick
2. Diederik P. Kingma
3. Karen Simonyan
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Christian Szegedy
7. Kaiming He
8. Andrew Zisserman
9. Ian J. Goodfellow
10. Yoshua Bengio

Papers from Parham Aarabi's perspective

Ordered by how strongly the researchers Parham Aarabi 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
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. Going deeper with convolutions

Their papers

• Adversarial Attacks on Face Detectors Using Neural Net Based Constrained Optimization (2018) — 95 citations
• LOHO: Latent Optimization of Hairstyles via Orthogonalization (2021) — 54 citations