Leabra7: a Python package for modeling recurrent, biologically-realistic neural networks

September 11, 2018 ยท Declared Dead ยท ๐Ÿ› arXiv.org

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Authors C. Daniel Greenidge, Noam Miller, Kenneth A. Norman arXiv ID 1809.04166 Category cs.NE: Neural & Evolutionary Cross-listed q-bio.NC Citations 0 Venue arXiv.org Last Checked 4 months ago
Abstract
Emergent is a software package that uses the AdEx neural dynamics model and LEABRA learning algorithm to simulate and train arbitrary recurrent neural network architectures in a biologically-realistic manner. We present Leabra7, a complementary Python library that implements these same algorithms. Leabra7 is developed and distributed using modern software development principles, and integrates tightly with Python's scientific stack. We demonstrate recurrent Leabra7 networks using traditional pattern-association tasks and a standard machine learning task, classifying the IRIS dataset.
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