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This issue serves as an umbrella issue for integrating networks from LTSF-Linear. Deep learning has proven to be an effective way to predict time series data. To expand this type of forecasting in skt…
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### Contact Details
manmeet.singh@utexas.edu
### Dataset description
Keeping continuous, long-term data to examine changes in urban surroundings is crucial as cities expand and develop. The DMSP OL…
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```
RuntimeError: Expected attn_mask dtype to be bool or to match query dtype, but got attn_mask.dtype: float and query.dtype: double instead.
```
Here's the complete call stack
```
Tracebac…
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It would be really great if we could get `sktime` to a state where we can easily replicate standard feature set benchmarks (e.g., time series classification) as presented by @benfulcher.
Example ex…
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"I read the blog post (https://huggingface.co/blog/zh/time-series-transformers) and I'm really confused about the evaluation metrics. I would be extremely grateful if I could get some help. Specifical…
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**Is your feature request related to a problem? Please describe.**
ARFIMA and various models for fractionally differenced models are useful in modelling low signal-to-noise ratio time series. Imple…
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Found based on the investigations in #4965 reported by @MCRE-BE
**Describe the bug**
The following code lead to strange results:
```python
import matplotlib.pyplot as plt
import pandas as …
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Hello,
Currently, COCA accepts datasets that are univariate. Is it possible to expand to multivariate?
Thanks,
Marcia
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Your work is an incredible resource for transformer architectures. They are well worn in the NLP domain and I have noticed their increase use with time-series.I have however also noticed a dearth of c…
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https://github.com/oliverguhr/transformer-time-series-prediction/blob/570d39bc0bbd61c823626ec9ca8bb5696c068187/transformer-multistep.py#L210