Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.

Overview

Conformal time-series forecasting

Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.

If you use our code in your research, please cite:

@inproceedings{stankeviciute2021conformal,
  author = {Stankevičiūtė, Kamilė and Alaa, Ahmed M. and {van der Schaar}, Mihaela},
  title = {Conformal time-series forecasting},
  booktitle = {Advances in Neural Information Processing Systems},
  year = {2021}
}

This codebase builds on the implementation for "Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence Functions" (ICML 2020), available at https://github.com/ahmedmalaa/rnn-blockwise-jackknife under the BSD 3-clause license.

Owner
Kamilė Stankevičiūtė
ML for Medicine PhD student @vanderschaarlab, University of Cambridge. Oxford MSc CS, ex-Google.
Kamilė Stankevičiūtė
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