vertaix/Alternators
This repository contains the implementation of **Alternators**, a novel family of generative models for time-dependent data.
Alternators helps researchers and data scientists generate realistic, synthetic time-dependent data, such as sensor readings, financial sequences, or biological signals. You provide existing time-series data, and it generates new, plausible sequences that reflect the underlying patterns, even for complex or chaotic systems. This is ideal for anyone who needs to simulate future scenarios or expand limited datasets without collecting more real-world observations.
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Use this if you need to create synthetic, dynamic data trajectories that accurately mimic complex time-series patterns, especially for chaotic or highly variable systems.
Not ideal if you are looking for simple forecasting of a single time series or if your data is not sequential and time-dependent.
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Python
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Last pushed
Jun 06, 2025
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