Inbar Huberman-Spiegelglas

Computer Vision and Pattern Recognition · 2023

A researcher in the Science corpus: 1 paper; trusts 51 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 24 citations into it
• Generative Models — 16 citations into it
• Artificial Intelligence — 5 citations into it
• Statistical and Nonlinear Physics — 5 citations into it

Whom Inbar Huberman-Spiegelglas trusts overall

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

1. Jonathan Ho
2. Prafulla Dhariwal
3. Diederik P. Kingma
4. Geoffrey E. Hinton
5. Jiaming Song
6. Alex Krizhevsky
7. Alex Nichol
8. Yoshua Bengio
9. Kaiming He
10. Yann LeCun

Papers from Inbar Huberman-Spiegelglas's perspective

Ordered by how strongly the researchers Inbar Huberman-Spiegelglas 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. ImageNet Large Scale Visual Recognition Challenge
8. Gradient-based learning applied to document recognition
9. GENERATIVE ADVERSARIAL NETS
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• An Edit Friendly DDPM Noise Space: Inversion and Manipulations (2023) — 297 citations