1sec.ai

Tag

#time-series

Every item tagged time-series, newest first.

3 items

modelsJan 19

PatchTSMixer in HuggingFace

PatchTSMixer, a new open-source time series forecasting model, has been released on the Hugging Face platform. It aims to improve forecasting accuracy and efficiency. The model is designed for practical applications, offering a balance between performance and computational resources. You can explore and use PatchTSMixer through the Hugging Face model hub.

Key takeaways
  • PatchTSMixer is an open-source time series forecasting model.
  • Released on the Hugging Face platform.
  • Aims for a balance between forecasting accuracy and efficiency.
researchJun 16

Yes, Transformers are Effective for Time Series Forecasting (+ Autoformer)

Researchers found that standard transformer architectures can be highly effective for time series forecasting tasks, challenging prior assumptions about their suitability. The Autoformer model, a transformer variant, achieved state-of-the-art results on several benchmarks. This shows that transformers can be a viable option for time series forecasting, offering a new perspective on the problem. You can explore transformer-based models for your forecasting needs.

Key takeaways
  • Transformers effective for time series forecasting, contrary to prior assumptions.
  • Autoformer achieves state-of-the-art results on multiple benchmarks.
  • Transformers offer a new perspective on time series forecasting problems.
toolsDec 1

Probabilistic Time Series Forecasting with 🤗 Transformers

Hugging Face released a probabilistic time series forecasting library using Transformers, enabling builders to generate uncertainty estimates for time series predictions. This library allows for more accurate and reliable forecasting by providing a range of possible outcomes. You can integrate it into your applications for better decision-making. The library is open-source and available for use.

Key takeaways
  • Enables probabilistic time series forecasting with Transformers.
  • Provides uncertainty estimates for more accurate predictions.
  • Open-source library available for integration.