Jonas Muller

Computer Vision and Pattern Recognition · 2023–2025

A researcher in the Science corpus: 3 papers; trusts 38 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 103 citations into it
• Generative Models — 56 citations into it
• Artificial Intelligence — 37 citations into it
• Statistical and Nonlinear Physics — 25 citations into it
• Probabilistic & Bayesian Methods — 10 citations into it

Whom Jonas Muller trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yoshua Bengio
5. Jonathan Ho
6. Kaiming He
7. Aapo Hyvärinen
8. Yann LeCun
9. Ilya Sutskever
10. Yang Song

Papers from Jonas Muller's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. ImageNet: A large-scale hierarchical image database
5. ImageNet Large Scale Visual Recognition Challenge
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Long Short-Term Memory
9. Gradient-based learning applied to document recognition
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis (2023) — 5,094 citations
• Scaling Rectified Flow Transformers for High-Resolution Image Synthesis (2024) — 4,349 citations
• FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space (2025) — 917 citations