Kilian Batzner
Artificial Intelligence · 2021–2023
A researcher in the Science corpus: 2 papers; trusts 173 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 60 citations into it
- Computer Vision and Pattern Recognition — 45 citations into it
- Radiology, Nuclear Medicine and Imaging — 14 citations into it
- Computer Networks and Communications — 12 citations into it
- Industrial and Manufacturing Engineering — 11 citations into it
- Model Architectures — 8 citations into it
- Biophysics — 6 citations into it
- Generative Models — 6 citations into it
Whom Kilian Batzner trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Paul Bergmann
- Alex Krizhevsky
- Diederik P. Kingma
- Kaiming He
- Geoffrey E. Hinton
- Ross B. Girshick
- Thomas Schlegl
- Carsten Steger
- Individualized Treat
- Yoshua Bengio
Papers from Kilian Batzner's perspective
Ordered by how strongly the researchers Kilian Batzner trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- The MVTec Anomaly Detection Dataset: A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection (2021) — 568 citations
- EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies (2023) — 362 citations