Matthias Zeppelzauer

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 19 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 25 citations into it; #23,798 of 35,345 by trust here, #25,809 by citations
• Safety, Robustness & Interpretability — 10 citations into it
• Privacy & Security — 9 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it

Whom Matthias Zeppelzauer trusts overall

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

1. Alex Krizhevsky
2. Yann LeCun
3. Kaiming He
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Pang Wei Koh
7. Yinzhi Cao
8. Aditya Golatkar
9. L. Eon Bottou

Who trusts Matthias Zeppelzauer overall

1. Aditya Golatkar

Papers from Matthias Zeppelzauer's perspective

Ordered by how strongly the researchers Matthias Zeppelzauer 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. Gradient-based learning applied to document recognition
3. Learning Multiple Layers of Features from Tiny Images
4. ImageNet classification with deep convolutional neural networks
5. ImageNet: A large-scale hierarchical image database
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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

• Machine unlearning: linear filtration for logit-based classifiers (2020) — 171 citations