Výsledky vyhledávání - "Alper Yegenoglu"

Akademický článek

Exploring Parameter and Hyper-Parameter Spaces of Neuroscience Models on High Performance Computers With Learning to Learn

Autor: Alper Yegenoglu, Anand Subramoney, Thorsten Hater, Cristian Jimenez-Romero, Wouter Klijn, Aarón Pérez Martín, Michiel van der Vlag, Michael Herty, Abigail Morrison, Sandra Diaz-Pier

Publikováno v: Frontiers in Computational Neuroscience, Vol 16 (2022)

Neuroscience models commonly have a high number of degrees of freedom and only specific regions within the parameter space are able to produce dynamics of interest. This makes the development of tools and strategies to efficiently find these regions

Externí odkaz: https://doaj.org/article/48f75b596f42417a9a8e08f9f36d2677

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Akademický článek

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE

Autor: Pietro Quaglio, Alper Yegenoglu, Emiliano Torre, Dominik M. Endres, Sonja Grün

Publikováno v: Frontiers in Computational Neuroscience, Vol 11 (2017)

Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs). STPs are hypothesized to play a role in the comm

Externí odkaz: https://doaj.org/article/5d9d9350cc39495f92a83c3a150be4c4

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Ensemble Kalman Filter Optimizing Deep Neural Networks: An Alternative Approach to Non-performing Gradient Descent

Autor: Alper Yegenoglu, Michael Herty, Sandra Diaz Pier, Kai Krajsek

Publikováno v: Cham : Springer, Lecture Notes in Computer Science 12566, 78-92 (2020). doi:10.1007/978-3-030-64580-9_7
Machine Learning, Optimization, and Data Science
Machine Learning, Optimization, and Data ScienceThe Sixth International Conference on Machine Learning, Optimization, and Data Science, LOD2020, Siena, Italy, 2020-07-19-2020-07-22
Machine Learning, Optimization, and Data Science ISBN: 9783030645793
LOD (2)
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Machine Learning, Optimization, and Data Science
Machine Learning, Optimization, and Data Science-6th International Conference, LOD 2020, Siena, Italy, July 19–23, 2020, Revised Selected Papers, Part II

The successful training of deep neural networks is dependent on initialization schemes and choice of activation functions. Non-optimally chosen parameter settings lead to the known problem of exploding or vanishing gradients. This issue occurs when g

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f40159bae9de89e79ba405ed8c3b4030
https://juser.fz-juelich.de/record/889208

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A Collaborative Simulation-Analysis Workflow for Computational Neuroscience Using HPC

Autor: Michael Denker, Anna Lührs, Andrew P. Davison, Daniel Zielasko, Vahid Rostami, David Lester, Sacha J. van Albada, Bernd Schuller, Benjamin Weyers, Markus Diesmann, Olivier Amblet, Sonja Grün, Andrew Rowley, Johanna Senk, Alan B. Stokes, Pietro Quaglio, Yury Brukau, Alper Yegenoglu

Publikováno v: Cham : Springer International Publishing, Lecture Notes in Computer Science 10164, 243-256 (2017). doi:10.1007/978-3-319-53862-4_21
High-Performance Scientific Computing / Di Napoli, Edoardo (Editor) ; Cham : Springer International Publishing, 2017, Chapter 21 ; ISSN: 0302-9743=1611-3349 ; ISBN: 978-3-319-53861-7=978-3-319-53862-4 ; doi:10.1007/978-3-319-53862-4
High-Performance Scientific Computing / Di Napoli, Edoardo (Editor) ; Cham : Springer International Publishing, 2017, Chapter 21 ; ISSN: 0302-9743=1611-3349 ; ISBN: 978-3-319-53861-7=978-3-319-53862-4 ; doi:10.1007/978-3-319-53862-4Jülich Aachen Research Alliance (JARA) High-Performance Computing Symposium, JHPCS '16, Aachen, Germany, 2016-10-04-2016-10-05
Lecture Notes in Computer Science ISBN: 9783319538617
JHPCS
Lecture Notes in Computer Science
Lecture Notes in Computer Science-High-Performance Scientific Computing

Workflows for the acquisition and analysis of data in the natural sciences exhibit a growing degree of complexity and heterogeneity, are increasingly performed in large collaborative efforts, and often require the use of high-performance computing (H

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::433089b0439c2fce26d92b0241b7bda7

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Exploring the Usefulness of Formal Concept Analysis for Robust Detection of Spatio-temporal Spike Patterns in Massively Parallel Spike Trains

Autor: Dominik Endres, Sonja Grün, Emiliano Torre, Pietro Quaglio, Alper Yegenoglu

Publikováno v: Graph-Based Representation and Reasoning ISBN: 9783319409849
ICCS
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Graph-Based Representation and Reasoning
Graph-Based Representation and Reasoning

The understanding of the mechanisms of information processing in the brain would yield practical impact on innovations such as brain-computer interfaces. Spatio-temporal patterns of spikes (or action potentials) produced by groups of neurons have bee

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0b3b9053eecbf6143a70889cb6f9352b
https://doi.org/10.1007/978-3-319-40985-6_1

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