Oliver Eberle

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 45 citations into it
• Graph Learning — 17 citations into it
• Safety, Robustness & Interpretability — 17 citations into it
• Computer Vision and Pattern Recognition — 16 citations into it
• Materials Chemistry — 14 citations into it

Whom Oliver Eberle trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Grgoire Montavon
4. Karen Simonyan
5. Yann LeCun
6. Yoshua Bengio
7. Alex Krizhevsky
8. Kristof T. Schütt
9. Ilya Sutskever
10. Jimmy Ba

Papers from Oliver Eberle's perspective

Ordered by how strongly the researchers Oliver Eberle 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
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. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Higher-Order Explanations of Graph Neural Networks via Relevant Walks (2020) — 310 citations