Thomas Leimkühler

Computer Vision and Pattern Recognition · 2023

A researcher in the Science corpus: 1 paper; trusts 102 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 41 citations into it
• Generative Models — 33 citations into it
• Artificial Intelligence — 8 citations into it

Whom Thomas Leimkühler trusts overall

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

1. Diederik P. Kingma
2. Tero Karras
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Kaiming He
6. Yoshua Bengio
7. Thomas Brox
8. Yann LeCun
9. Jimmy Ba
10. Ilya Sutskever

Papers from Thomas Leimkühler's perspective

Ordered by how strongly the researchers Thomas Leimkühler 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. GENERATIVE ADVERSARIAL NETS
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Long Short-Term Memory
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold (2023) — 366 citations