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Hebel - GPU-Accelerated Deep Learning Library in Python

Name: Hebel - GPU-Accelerated Deep Learning Library in Python
Creator: Hannes Bretschneider
Keywords: machine learning, gpu, cuda, deep learning, computer science, neural networks

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 22 May 2014Publisher:Zenodo

Authors: Hannes Bretschneider;

doi: 10.5281/zenodo.10050

Hebel - GPU-Accelerated Deep Learning Library in Python

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Abstract

Hebel is a library for deep learning with neural networks in Python using GPU acceleration with CUDA through PyCUDA. It implements the most important types of neural network models and offers a variety of different activation functions and training methods such as momentum, Nesterov momentum, dropout, and early stopping.

Related Organizations

University of Toronto
Canada

Keywords

machine learning, gpu, cuda, deep learning, computer science, neural networks

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	1
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average

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Related to Research communities

UArctic