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https://arxiv.org/pdf/2310.10688.pdf
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1. How to select an ideal forecasting method? (~ Ward et al. 2014)
* evaluate forecasting approaches across different time series
* do time series properties influence which methods (or para…
ha0ye updated
5 years ago
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Hello TensorFlow Probability Team,
I'm using the Structural Time Series (STS) module for time series forecasting, specifically with a model that includes a `LinearRegression` component for exogenou…
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- PyTorch-Forecasting version: 0.10.3
- PyTorch version: 1.13.1+cu116
- Python version: 3.8.10
- Operating System: Linux-5.10.147+-x86_64-with-glibc2.29
### Expected behavior
I executed the t…
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Large question, and requires some discussion and then some planning. But as it keeps coming up, I think we need to discuss it:
Basic question is, should we rename the current `fmu.iteration` to `fm…
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I tried making the target stationary to account for extrapolation issues with tree-based models but encountered a frequency inference error and had to manually set a frequency of "30min".
https://…
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## Detailed Description
Diffusion models seem to be quite useful for a lot of image generation and high detail and much easier training than for GANs as generative models, e.g. StableDiffusion. Thi…
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**Describe the bug**
When fitting N models one for each forecasting horizon using **make_reduction** with **strategy="direct"** and **pooling="global"**, the dataset that is used to train the model…
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The goal is to investigate how to implement the `GraphCast` ML model as service:
* Create a new repo containing the solution
* in a Docker container
* on demand
* with GPU enabled if available
* with…
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The data in such function:
```python
def generate_numerical(raw_folder, save_path, mode="test", obs_length=15):
raw_data = np.load(os.path.join(raw_folder, "sg_raw_" + mode + ".npy"))
da…