Frieder Ganz

Artificial Intelligence · 2019

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 28 citations into it
• Computer Vision and Pattern Recognition — 14 citations into it
• Representation & Self-Supervised Learning — 9 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it
• Reinforcement Learning — 5 citations into it

Whom Frieder Ganz trusts overall

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

1. Friedemann Zenke
2. Nitin Kamra
3. Geoffrey E. Hinton
4. Douglas A. Reynolds
5. Michal Wozniak
6. Alex Krizhevsky
7. Ronald Kemker

Papers from Frieder Ganz's perspective

Ordered by how strongly the researchers Frieder Ganz 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. Gradient-based learning applied to document recognition
4. Dropout: a simple way to prevent neural networks from overfitting
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
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

• Continual Learning in Deep Neural Network by Using a Kalman Optimiser (2019) — 5 citations
• Continual Learning Using Bayesian Neural Networks (2019) — 46 citations