Hamid Kazemi

Computer Vision and Pattern Recognition · 2022–2024

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 29 citations into it
• Generative Models — 24 citations into it

Whom Hamid Kazemi trusts overall

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

1. Alex Krizhevsky
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Yann LeCun
5. Yoshua Bengio
6. Prafulla Dhariwal

Papers from Hamid Kazemi's perspective

Ordered by how strongly the researchers Hamid Kazemi trusts endorse each paper. Same corpus, a different order for every researcher.

1. Gradient-based learning applied to document recognition
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Learning Multiple Layers of Features from Tiny Images
5. GENERATIVE ADVERSARIAL NETS
6. Attention is All you Need (Neural Information Processing Systems)
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
9. Long Short-Term Memory
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text (2024) — 325 citations
• Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise (2022) — 440 citations