Urs M. Bergmann

Computer Vision and Pattern Recognition · 2016–2021

A researcher in the Science corpus: 3 papers; trusts 205 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 61 citations into it; #11,431 of 21,575 by trust here, #10,334 by citations
• Computer Graphics and Computer-Aided Design — 26 citations into it; #798 of 1,584 by trust here, #605 by citations
• Generative Models — 26 citations into it; #1,379 of 1,956 by trust here, #1,635 by citations
• Artificial Intelligence — 13 citations into it
• Model Architectures — 7 citations into it

Whom Urs M. Bergmann trusts overall

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

1. Alexei A. Efros
2. Diederik P. Kingma
3. Alec Radford
4. Geoffrey E. Hinton
5. Individualized Treat
6. Javier Portilla
7. Alex Krizhevsky
8. Luke Metz
9. Leon A. Gatys
10. Jimmy Ba

Who trusts Urs M. Bergmann overall

1. Abdul Jabbar
2. Jie Gui
3. Xi Li
4. Ning Yu
5. Zhengwei Wang
6. Tamar Rott Shaham
7. Eric Laloy
8. Bourahla Omar

Papers from Urs M. Bergmann's perspective

Ordered by how strongly the researchers Urs M. Bergmann 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. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations (2021) — 260 citations
• Learning Texture Manifolds with the Periodic Spatial GAN (2017) — 179 citations
• Texture Synthesis with Spatial Generative Adversarial Networks (2016) — 226 citations