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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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I experienced that compared to Transformers, Mamba model has large variance in performance with respect to model initialization. Did you guys also noticed this?
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### Description
According to "Anomaly scoring is based on overlapping segments: a true positive (TP) if a known anomalous window overlaps any detected windows, a false negative (FN) if a known anomal…
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Another foundation model we could interface is LagLLama: https://github.com/time-series-foundation-models/lag-llama
While the weights are hosted on HuggingFace, I suppose that they are not usable w…
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Hi! We're implementing some transformer architectures like [Gated Transformer Networks for Multivariate Time Series Classification](https://arxiv.org/abs/2103.14438). Are you interested in pulling mor…
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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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## About
At [^1][^2], we shared a few notes about time series anomaly detection, and forecasting/prediction. Other than using traditional statistics-based time series forecasting methods like [Holt…
amotl updated
4 months ago
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Hello! Your transformer is amazing! But i m beginner in data science. I have to do research for my university task: we want to predict how negotiations will finish. We have various modalities includin…
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### **Describe the bug**
When I attempt to run the `TransformerModel` using multiple GPUs, I encounter the following error:
```
RuntimeError: unsupported operation: some elements of the input ten…
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We should ensure that pipelines between annotators, transformers, and other estimators integrate seamlessly.
We should cover:
* concatenating annotation estimators with transformations
* concat…