In-context Bayesian Learning Curve Extrapolation
Project description
Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks
This repository offers an implementation of LC-PFN, a method designed for efficient Bayesian learning curve extrapolation.
LC-PFN in action on Google colab and HuggingFace
Installation using pip:
pip install -U lcpfn
Usage
Try out the notebooks
(require matplotlib
) for training and inference examples.
NOTE: Our model supports only increasing curves with values in $[0,1]$. If needed, please consider normalizing your curves to meet these constraints. See an example in notebooks/curve_normalization.ipynb
.
Reference
@inproceedings{
adriaensens2023lcpfn,
title={Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks},
author={Adriaensen, Steven and Rakotoarison, Herilalaina and Müller, Samuel and Hutter, Frank},
booktitle={Thirty-seventh Conference on Neural Information Processing Systems},
year={2023},
url={https://openreview.net/forum?id=xgTV6rmH6n}
}
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
lcpfn-0.1.3.tar.gz
(29.2 kB
view hashes)
Built Distribution
lcpfn-0.1.3-py3-none-any.whl
(32.3 kB
view hashes)