Ammar-Raneez/Liquid-Time-stochasticity-networks
Code repository for Liquid Time-stochasticity networks (LTSs)
This project helps researchers and data scientists working with time-series data, especially when dealing with unpredictable or 'stochastic' patterns. It takes in sequential data, like financial market prices or sensor readings, and produces models capable of predicting future values based on past observations. This is ideal for those needing to analyze and forecast complex, time-dependent systems.
No commits in the last 6 months.
Use this if you need to build advanced predictive models for time-series data that exhibit high variability and non-linear behavior.
Not ideal if you are looking for a simple, off-the-shelf solution for basic time-series forecasting without deep learning expertise.
Stars
23
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5
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Apr 26, 2023
Commits (30d)
0
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