AQDiff
Adaptive Quantile Diffusion (AQDiff) Showcase
About AQDiff
AQDiff tackles real-world time series forecasting—particularly in high-stakes domains like pandemic prediction. It leverages diffusion models to produce probabilistic forecasts, and continuously recalibrates those forecasts based on recent residual errors. By adaptively shifting the target quantile parameter, the model refines its predictions and maintains more stable uncertainty bounds.
In essence, AQDiff helps:
- Capture complex temporal dynamics with diffusion
- Adapt forecasts in real-time through an adaptive quantile equation
- Improve forecast reliability for applications like epidemiological modeling.
The Paper was submitted to the Knowledge Discovery Dataset conference. The Print of the paper is available here
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layout: page title: project description: a project with a background image img: /assets/img/AQDiff.png —




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