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Awesome GitHub RepositoriesConvolutional Sequence Models
Sequence models that utilize stacks of convolutional layers instead of recurrent units for parallel processing.
Distinct from Sequence-to-Sequence Models: Distinct from general Sequence-to-Sequence Models: specifically focuses on the convolutional architecture rather than encoder-decoder patterns.
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Awesome Convolutional Sequence Models GitHub Repositories
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- locuslab/tcn
locuslab/TCN
4,525Voir sur GitHubTCN is a deep learning sequence framework and library for building temporal convolutional networks. It provides a toolkit for implementing purely convolutional architectures to model sequential data as an alternative to recurrent neural networks. The project includes a sequence modeling benchmark suite designed to evaluate the accuracy and processing speed of architectures. This suite utilizes standardized tasks, including memory problems, digit classification, music, and language tasks, to quantify performance. The framework covers a range of structural components for sequence processing, s
Replaces recurrent neural networks with a stack of convolutional layers to allow parallel processing of sequences.
Python
