Abstract
Developing effective learning systems for Machine Learning (ML) applications in the Neuromorphic (NM) field requires extensive experimentation and simulation. Software frameworks aid and ease this process by providing a set of ready-to-use tools that researchers can leverage. The recent interest in NM technology has seen the development of several new frameworks that do this, and that add up to the panorama of already existing libraries that belonged to neuroscience fields. This work reviews 9 frameworks for the development of Spiking Neural Networks (SNNs) that are specifically oriented towards data science applications. Furthermore, we present an extension to the SpykeTorch framework that gives users access to a much broader choice of spiking neurons to embed in SNNs and make the code publicly available.
Original language | English |
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Number of pages | 8 |
Publication status | Submitted - 13 Jun 2022 |
Event | International Conference On Neuromorphic Systems 2022 - Knoxville, United States Duration: 27 Jul 2022 → 29 Jul 2022 |
Conference
Conference | International Conference On Neuromorphic Systems 2022 |
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Abbreviated title | ICONS 2022 |
Country/Territory | United States |
City | Knoxville |
Period | 27/07/22 → 29/07/22 |
Keywords
- frameworks
- spiking neural networks
- spiking neurons
- algorithms
- neuromorphic