Profil Alex Sarishvili

Schwerpunkte/Kompetenzen

• Machine Learning, Deep Learning
  
• Bayessche und Chow-Liu-Netze
• Neuronale Netze
  
• Statistische Lerntheorie

 

Publikationen

Highlightpublikationen

• Gramsch, S.; Sarishvili, A.; Schmeißer, A.:
  Analysis of the Fiber Laydown Quality in Spunbond Processes with Simulation Experiments Evaluated by Blocked Neural Networks
  In: Advances in Polymer Technology Vol 3 (2020).
  
• Sarishvili, A.; Winter, J.; Luhmann, H. J.; Mildenberger, E.:
  Probabilistic graphical model identifies clusters of EEG patterns in recordings from neonates.
  In: Clinical Neurophysiology 130, Pages 1342-1350 (2019).
  
• Sarishvili, A.; Wirsen, A.; Jirstrand, M.:
  On Chow-Liu forest based regularization of deep belief networks.
  28th International Conference on Artificial Neural Networks and Machine Learning ICANN 2019: Workshop and Special Sessions.
  In: Lecture Notes in Computer Science (LNCS, volume 11731) Pages 353-364 (2019).
  
• Sarishvili, A.; Hanselmann, G.:
  Software Reliability prediction via two different implementations of Bayesian model averaging.
  ECML/PKDD 2013, European conference on machine learning and principles and practice of knowledge discovery in databases.
  In: Workshop Proceedings COPEM2013: Solving complex machine learning problems with ensamble methods. Prag (2013).
• Sarishvili, A.; Andersson, Ch.; Franke, J.; Kroisandt, G.:
  On the Consistency of the Blocked Neural Network Estimator in Time Series Analysis.
  In: Neural Computation 18, Volume 10, Pages 1-14 (2006).