Stefan H. Sack

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 43 citations into it
• Atomic and Molecular Physics, and Optics — 18 citations into it
• Optimization & Training — 6 citations into it

Whom Stefan H. Sack trusts overall

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

1. Edward Farhi
2. Maria Schuld
3. Diederik P. Kingma
4. Geoffrey E. Hinton
5. David E. Rumelhart
6. Bernhard Schölkopf
7. Giuseppe Carleo

Papers from Stefan H. Sack's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Learning representations by back-propagating errors
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. A Stochastic Approximation Method
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Attention is All you Need (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. Multilayer feedforward networks are universal approximators

Their papers

• Parameterized quantum circuits as machine learning models (2019) — 1,332 citations