Sebastian J. Wirkert

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 2 papers; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 37 citations into it
• Artificial Intelligence — 34 citations into it
• Generative Models — 24 citations into it
• Probabilistic & Bayesian Methods — 16 citations into it
• Statistics and Probability — 6 citations into it

Whom Sebastian J. Wirkert trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Max Welling
5. Alex Krizhevsky
6. Tim Salimans
7. Laurent Dinh
8. Kaiming He
9. Radford M. Neal
10. Yann LeCun

Papers from Sebastian J. Wirkert's perspective

Ordered by how strongly the researchers Sebastian J. Wirkert 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet: A large-scale hierarchical image database
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation (2018) — 1,100 citations
• Analyzing Inverse Problems with Invertible Neural Networks (2018) — 598 citations