Franz-Josef Pfreundt

Artificial Intelligence · 2015–2016

A researcher in the Science corpus: 2 papers; trusts 56 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it
• Optimization & Training — 14 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it

Whom Franz-Josef Pfreundt trusts overall

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

1. Alex Krizhevsky
2. L. Eon Bottou
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Anil K. Jain
6. David Sculley
7. Forrest N. Iandola
8. Ilya Sutskever
9. Quoc V. Le
10. Christian Szegedy

Papers from Franz-Josef Pfreundt's perspective

Ordered by how strongly the researchers Franz-Josef Pfreundt 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. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Going deeper with convolutions
7. ImageNet: A large-scale hierarchical image database
8. Attention is All you Need (Neural Information Processing Systems)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Distributed Training of Deep Neural Networks: Theoretical and Practical Limits of Parallel Scalability (2016) — 104 citations
• Asynchronous parallel stochastic gradient descent: a numeric core for scalable distributed machine learning algorithms (2015) — 38 citations