- Mar 20, 2019
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Martin Beseda authored
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Martin Beseda authored
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Martin Beseda authored
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- Mar 19, 2019
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Michal Kravcenko authored
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- Jan 06, 2019
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Martin Beseda authored
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- Dec 29, 2018
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Martin Beseda authored
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- Oct 04, 2018
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David Vojtek authored
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- Sep 26, 2018
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David Vojtek authored
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- Sep 20, 2018
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Martin Beseda authored
ENH: Only classes belonging to API are now contained in 4neuro.h. All those classes were enclosed in 'lib4neuro' namespace.
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- Sep 19, 2018
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Michal Kravcenko authored
ADD: added preliminary version of gradient calculation vie backpropagation, added supporting methods to error classes and learning algorithms utilizing gradient calculation
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- Sep 18, 2018
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Martin Beseda authored
ENH: Removed both linking and include dependencies from examples => lib4neuro can be used just by linking it and including its header without any external dependencies needed.
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Martin Beseda authored
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- Sep 14, 2018
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Martin Beseda authored
FIX: Fixed Boost include dependencies, so the examples don't have to be compiled with Boost include directory.
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- Aug 30, 2018
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kra568 authored
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- Aug 13, 2018
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Martin Beseda authored
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- Aug 10, 2018
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Michal Kravcenko authored
Updated the structure and functionality of NeuralNEtwork class to account for the changes in connections and neurons. Updated the logic in DESolver to account for the changes in NeuralNetwork
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- Aug 09, 2018
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Michal Kravcenko authored
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- Jul 24, 2018
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Michal Kravcenko authored
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- Jul 18, 2018
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Michal Kravcenko authored
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- Jul 17, 2018
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Michal Kravcenko authored
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- Jul 16, 2018
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Michal Kravcenko authored
-added an example testing multi-network error function
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Martin Beseda authored
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- Jul 13, 2018
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David Vojtek authored
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- Jun 15, 2018
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Michal Kravcenko authored
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Michal Kravcenko authored
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- Jun 14, 2018
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Michal Kravcenko authored
- Added preliminary connection classes with neural network class able to evaluate inputs via the feed-forward method. - Added a test case for validating feed-forward capabilities of our networks
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- Jun 13, 2018
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Michal Kravcenko authored
preliminary work on connections, neural networks and neurons with neural networks as activation functions
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