Joerg Evermann

Artificial Intelligence · 2013–2016

A researcher in the Science corpus: 2 papers; trusts 35 researchers and is trusted by 30 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 16 citations into it
• Management Science and Operations Research — 9 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it
• Organizational Behavior and Human Resource Management — 8 citations into it; #843 of 8,741 by trust here, #3,407 by citations
• Sociology and Political Science — 7 citations into it
• Statistics and Probability — 7 citations into it
• Accounting — 6 citations into it
• Model Architectures — 6 citations into it

Whom Joerg Evermann trusts overall

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

1. Ilya Sutskever
2. Geoffrey E. Hinton
3. David Ruppert
4. J. Urgen Schmidhuber
5. Alex Graves
6. Jörg Henseler
7. L. V. D. van der Maaten
8. Wojciech Zaremba
9. Yoshua Bengio
10. Andrej Karpathy

Who trusts Joerg Evermann overall

1. Mikko Rönkkö
2. Marko Sarstedt
3. Christian M. Ringle
4. Asyraf Afthanorhan
5. Joseph F. Hair
6. Jörg Henseler
7. Hendrik Strobelt
8. Hamdollah Ravand
9. Edward E. Rigdon
10. C. Mcintosh

Papers from Joerg Evermann's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Predicting process behaviour using deep learning (2016) — 407 citations
• A Critical Examination of Common Beliefs About Partial Least Squares Path Modeling (2013) — 422 citations