Matthias Reisser

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 20 citations into it; #23,997 of 35,345 by trust here, #28,481 by citations
• Computer Vision and Pattern Recognition — 20 citations into it; #14,845 of 21,575 by trust here, #18,266 by citations

Whom Matthias Reisser trusts overall

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

1. Yoshua Bengio
2. Kaiming He
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Yann LeCun
6. Diederik P. Kingma
7. Chris J. Maddison
8. Eric Jang
9. X. Zhang
10. Antonio Polino

Who trusts Matthias Reisser overall

1. Markus Nagel
2. Mart van Baalen
3. Tijmen Blankevoort
4. Alexandre D'efossez
5. Ying Wang

Papers from Matthias Reisser's perspective

Ordered by how strongly the researchers Matthias Reisser 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. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Relaxed Quantization for Discretized Neural Networks (2018) — 149 citations