| Year |
Citation |
Score |
| 2014 |
Latorre JI, El-Laithy K, Bogdan M, Jiménez E. Development of a petri net model for a reconfigurable intelligent system based on experimental data 26th European Modeling and Simulation Symposium, Emss 2014. 608-612. |
0.388 |
|
| 2012 |
El-Laithy K, Knorr M, Käs J, Bogdan M. Digital detection and analysis of branching and cell contacts in neural cell cultures. Journal of Neuroscience Methods. 210: 206-19. PMID 22841629 DOI: 10.1016/J.Jneumeth.2012.07.007 |
0.541 |
|
| 2012 |
El-Laithy K, Bogdan M. Temporal finite-state machines: A novel framework for the general class of dynamic networks Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7664: 425-434. DOI: 10.1007/978-3-642-34481-7_52 |
0.499 |
|
| 2012 |
Hoffmann J, Güttler F, El-Laithy K, Bogdan M. Cyfield-RISP: Generating dynamic instruction set processors for reconfigurable hardware using OpenCL Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7552: 169-176. DOI: 10.1007/978-3-642-33269-2_22 |
0.399 |
|
| 2011 |
El-Laithy K, Bogdan M. A reinforcement learning framework for spiking networks with dynamic synapses. Computational Intelligence and Neuroscience. 2011: 869348. PMID 22046180 DOI: 10.1155/2011/869348 |
0.588 |
|
| 2011 |
El-Laithy K, Bogdan M. On the capacity of transient internal states in liquid-state machines Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6792: 56-63. DOI: 10.1007/978-3-642-21738-8_8 |
0.414 |
|
| 2011 |
El-Laithy K, Bogdan M. A hypothetical free synaptic energy function and related states of synchrony Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6792: 40-47. DOI: 10.1007/978-3-642-21738-8_6 |
0.474 |
|
| 2010 |
El-Laithy K, Bogdan M. A hebbian-based reinforcement learning framework for spike-timing-dependent synapses Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6353: 160-169. DOI: 10.1007/978-3-642-15822-3_21 |
0.483 |
|
| 2010 |
Hoffmann J, El-Laithy K, Güttler F, Bogdan M. Simulating biological-inspired spiking neural networks with OpenCL Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6352: 184-187. DOI: 10.1007/978-3-642-15819-3_23 |
0.463 |
|
| 2010 |
El-Laithy K, Bogdan M. Predicting spike-timing of a thalamic neuron using a stochastic synaptic model Proceedings of the 18th European Symposium On Artificial Neural Networks - Computational Intelligence and Machine Learning, Esann 2010. 357-362. |
0.474 |
|
| 2009 |
El-Laithy K, Bogdan M. Synchrony state generation in artificial neural networks with stochastic synapses Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5768: 181-190. DOI: 10.1007/978-3-642-04274-4_19 |
0.547 |
|
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