Michael Färber

Artificial Intelligence · with Kaliszyk · 2016

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 16 citations into it
• Computational Theory and Mathematics — 9 citations into it
• Economics and Econometrics — 5 citations into it
• Program Analysis & Verification — 5 citations into it
• Reinforcement Learning — 5 citations into it

Whom Michael Färber trusts overall

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

1. Frank Hutter
2. J. Otten
3. Levente Kocsis
4. David Silver
5. Sylvain Gelly
6. Holger H. Hoos
7. Michael Norrish
8. Kevin Leyton-Brown
9. Csaba Szepesvari
10. M. Wenzel

Who trusts Michael Färber overall

1. Cezary Kaliszyk
2. Josef Urban

Papers from Michael Färber's perspective

Ordered by how strongly the researchers Michael Färber trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. Learning Multiple Layers of Features from Tiny Images
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. ImageNet: A large-scale hierarchical image database
9. Long Short-Term Memory
10. Going deeper with convolutions

Their papers

• Monte Carlo Connection Prover (2016) — 5 citations
• Monte Carlo Tableau Proof Search (2016) — 15 citations