Dr. Matthias Seeger

Artificial Intelligence · 2016

A researcher in the Science corpus: 1 paper; trusts 26 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 10 citations into it
• Computational Mechanics — 6 citations into it
• Optimization & Training — 5 citations into it
• Statistics and Probability — 5 citations into it

Whom Dr. Matthias Seeger trusts overall

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

1. Shai Shalev-Shwartz
2. Robert Tibshirani
3. Muthu Dayalan
4. Tong Zhang
5. Cho-Jui Hsieh
6. Galen Andrew
7. Ilya Trofimov
8. Bernhard E. Boser
9. Guo-Xun Yuan
10. Steve Webb

Who trusts Dr. Matthias Seeger overall

1. Celestine Mendler-Dünner
2. Simone Forte
3. Virginia Smith
4. Martin Takác
5. Martin Jaggi

Papers from Dr. Matthias Seeger's perspective

Ordered by how strongly the researchers Dr. Matthias Seeger 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• Distributed Optimization for Non-Strongly Convex Regularizers (2016)