Robin Sandkühler
Computer Vision and Pattern Recognition · 2021–2022
A researcher in the Science corpus: 2 papers; trusts 29 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 33 citations into it
- Artificial Intelligence — 22 citations into it
- Generative Models — 20 citations into it
- Biophysics — 8 citations into it
- Statistical and Nonlinear Physics — 8 citations into it
- Signal Processing — 7 citations into it
- Probabilistic & Bayesian Methods — 5 citations into it
Whom Robin Sandkühler trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Nichol
- Prafulla Dhariwal
- Jonathan Ho
- Diederik P. Kingma
- Alex Kendall
- Jiaming Song
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Kaiming He
Who trusts Robin Sandkühler overall
Papers from Robin Sandkühler's perspective
Ordered by how strongly the researchers Robin Sandkühler 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
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Diffusion Models for Implicit Image Segmentation Ensembles (2021) — 422 citations
- Diffusion Models for Medical Anomaly Detection (2022) — 417 citations