Franz Pernkopf

Artificial Intelligence · 2011–2020

A researcher in the Science corpus: 4 papers; trusts 160 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it; #32,971 of 35,345 by trust here, #33,294 by citations
• Computer Vision and Pattern Recognition — 20 citations into it
• Signal Processing — 15 citations into it; #7,122 of 7,572 by trust here, #6,836 by citations
• Model Architectures — 12 citations into it
• Probabilistic & Bayesian Methods — 10 citations into it
• Optimization & Training — 9 citations into it
• Representation & Self-Supervised Learning — 9 citations into it
• Generative Models — 6 citations into it

Whom Franz Pernkopf trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Yann LeCun
4. Hugo Larochelle
5. Diederik P. Kingma
6. Ruslan Salakhutdinov
7. Alex Krizhevsky
8. Kaiming He
9. Ilya Sutskever
10. Alex Graves

Who trusts Franz Pernkopf overall

1. Jochen Gast
2. Guillaume Alain
3. Stefan Roth

Papers from Franz Pernkopf's perspective

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

Their papers

• A Probabilistic Interaction Model for Multipitch Tracking With Factorial Hidden Markov Models (2011) — 67 citations
• Multi-channel lung sound classification with convolutional recurrent neural networks (2020) — 76 citations
• Variational Inference in Neural Networks using an Approximate Closed-Form Objective (2016) — 14 citations
• General Stochastic Networks for Classification (2014) — 22 citations