Bernhard C. Geiger

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 22 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it
• Representation & Self-Supervised Learning — 6 citations into it
• Safety, Robustness & Interpretability — 5 citations into it

Whom Bernhard C. Geiger trusts overall

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

1. Naftali Tishby
2. Alexander A. Alemi
3. Ravid Shwartz-Ziv
4. Ian S. Fischer
5. Yoshua Bengio
6. Geoffrey E. Hinton
7. Andrew M. Saxe
8. Jonathan Frankle
9. Diederik P. Kingma
10. Alex Krizhevsky

Papers from Bernhard C. Geiger's perspective

Ordered by how strongly the researchers Bernhard C. Geiger 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. Gradient-based learning applied to document recognition
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Learning Multiple Layers of Features from Tiny Images
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Learning Representations for Neural Network-Based Classification Using the Information Bottleneck Principle (2018) — 220 citations