kyegomez/LiqudNet
Implementation of Liquid Nets in Pytorch
This project offers a straightforward implementation of Liquid Time-constant Networks (LTCNs) in PyTorch, which are advanced neural network architectures designed for processing sequential data and time series. It takes numerical input data, often representing sequences or sensor readings, and produces outputs that capture dynamic patterns and predictions. Data scientists, machine learning engineers, and researchers working with complex, time-dependent datasets would use this.
Use this if you are a machine learning practitioner looking to experiment with or apply Liquid Time-constant Networks for tasks involving sequential data in a PyTorch environment.
Not ideal if you are a business user or domain expert without a background in deep learning, as this is a developer-focused tool requiring coding knowledge.
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69
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11
Language
Python
License
MIT
Category
Last pushed
Jan 31, 2026
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0
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