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### Project Name
ProactiveOS: AI-Driven Autonomous OS Management
### Description
Description:
ProactiveOS is an advanced AI-driven operating system management solution designed to enhance system st…
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It would be interesting to have the ability to extend the linear regression plot line beyond the input data to enable forecasting/predictions on linear models.
Ref. https://talk.observablehq.com/t/…
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Timegrad is a relatively new model that uses Autoregressive Denoising Diffusion for Multivariate Probabilistic Time Series Forecasting Link to paper [here](https://arxiv.org/pdf/2101.12072.pdf) . It h…
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As a first step into time series forecasting, add an R wrapper into deep learning to forecast.
A common use of neural networks in forecasting is to take the prior period values as columns and run …
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These will need a read for comparison
Owens 2008 Metrics for solar wind prediction models: Comparison of empirical, hybrid, and physics‐based schemes with 8 years of L1 observations: https://agupubs.…
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**Is your feature request related to a problem? Please describe.**
I'm always frustrated when trying to train forecasting models because it is slow and not using all my CPU cores.
**Describe the s…
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I think there is no reason transformer models are limited to past covariates.
As RNNs does, I think transformer also can treat future covariates and hstoric future covariates.
Is there any reas…
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### What happened + What you expected to happen
1. The bug when switching from one GPU core to anything with >1 cores:
```python
ValueError Traceback (most recent c…
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Hello,
I was adding exogenous regressors to the forecasting hierarchy using ARIMA model and formula notation. It works well when the exogenous values are added to all levels in a hierarchy.
**H…
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## What / Why
### What are we building?
The ML-Commons plugin allows user to upload deep learning models and use them to make inference.
### Why are we building it?
In many domains like…