Matthias Preindl

Automotive Engineering · with Chemali · 2018

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Automotive Engineering — 18 citations into it; #1,708 of 3,081 by trust here, #1,463 by citations
• Electrical and Electronic Engineering — 16 citations into it; #9,948 of 16,539 by trust here, #8,038 by citations
• Control and Systems Engineering — 9 citations into it
• Artificial Intelligence — 8 citations into it

Whom Matthias Preindl trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yann LeCun
4. Yoshua Bengio
5. Ilya Sutskever
6. Sepp Hochreiter
7. Mohammad Charkhgard
8. Wojciech Zaremba

Who trusts Matthias Preindl overall

1. Carlos Vidal

Papers from Matthias Preindl's perspective

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

1. Long Short-Term Memory
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
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. Going deeper with convolutions
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• State-of-charge estimation of Li-ion batteries using deep neural networks: A machine learning approach (2018) — 690 citations
• Long Short-Term Memory Networks for Accurate State-of-Charge Estimation of Li-ion Batteries (2018) — 687 citations