Martin Aumüller

Computer Vision and Pattern Recognition · 2018–2025

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 31 citations into it

Whom Martin Aumüller trusts overall

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

1. Yann LeCun
2. Jingdong Wang
3. L. Eon Bottou
4. Yoshua Bengio
5. Geoffrey E. Hinton
6. David G. Lowe
7. Ryan Williams
8. Alex Krizhevsky
9. Kaiming He
10. Ilya Sutskever

Who trusts Martin Aumüller overall

1. Wayne Xin Zhao
2. Thiago Akio Nakamura
3. Mengzhao Wang
4. Bhaskar Mitra
5. Ruiqi Guo
6. Jing Liu
7. Pedro H. Calais
8. Xiaoliang Xu
9. Corby Rosset
10. Philip Sun

Papers from Martin Aumüller's perspective

Ordered by how strongly the researchers Martin Aumüller trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Attention is All you Need (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• VIBE: Vector Index Benchmark for Embeddings (2025)
• ANN-Benchmarks: A Benchmarking Tool for Approximate Nearest Neighbor Algorithms (2018) — 590 citations