Andreas Nürnberger

Artificial Intelligence · 2005–2020

A researcher in the Science corpus: 4 papers; trusts 60 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 62 citations into it; #21,356 of 35,345 by trust here, #15,004 by citations
• Computer Vision and Pattern Recognition — 41 citations into it
• Information Systems — 17 citations into it; #6,694 of 8,771 by trust here, #6,501 by citations
• Model Architectures — 12 citations into it
• Probabilistic & Bayesian Methods — 12 citations into it
• Natural Language Processing — 11 citations into it
• Management Science and Operations Research — 10 citations into it
• Information Retrieval & Search — 9 citations into it

Whom Andreas Nürnberger trusts overall

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

1. Alex Krizhevsky
2. Andrew McCallum
3. Geoffrey E. Hinton
4. Yarin Gal
5. Diederik P. Kingma
6. Eric R. Ziegel
7. Teuvo Kohonen
8. Christian Szegedy
9. J. Ross Quinlan
10. Zoubin Ghahramani

Who trusts Andreas Nürnberger overall

1. David Martens
2. Donggeun Yoo

Papers from Andreas Nürnberger's perspective

Ordered by how strongly the researchers Andreas Nürnberger 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. ImageNet: A large-scale hierarchical image database
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Learning Multiple Layers of Features from Tiny Images
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
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

• The Power of Ensembles for Active Learning in Image Classification (2018) — 763 citations
• CHAOS Challenge - Combined (CT-MR) Healthy Abdominal Organ Segmentation (2020) — 882 citations
• A comparative analysis of offline and online evaluations and discussion of research paper recommender system evaluation (2013) — 159 citations
• A Brief Survey of Text Mining (2005) — 1,025 citations