Nabil Al-Bulushi

2009

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

Whom Nabil Al-Bulushi trusts overall

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

1. Martin A. Riedmiller
2. M. Gevrey
3. I. Dimopoulos

Papers from Nabil Al-Bulushi's perspective

Ordered by how strongly the researchers Nabil Al-Bulushi trusts endorse each paper. Same corpus, a different order for every researcher.

1. A direct adaptive method for faster backpropagation learning: the RPROP algorithm
2. Neural Networks: A Comprehensive Foundation
3. Review and comparison of methods to study the contribution of variables in artificial neural network models
4. Adaptive pattern recognition and neural networks
5. Learning representations by back-propagating errors
6. Neural Networks and the Bias/Variance Dilemma
7. Rectified Linear Units Improve Restricted Boltzmann Machines
8. Learning Multiple Layers of Features from Tiny Images
9. Gradient-based learning applied to document recognition
10. An empirical study of learning speed in back-propagation networks

Their papers

• Development of artificial neural network models for predicting water saturation and fluid distribution (2009) — 89 citations