Deep Learning in the Sequence Space

This repository accompanies the paper Deep Learning in the Sequence Space by Marlon Azinovic-Yang and Jan Žemlička.

It contains the notebook 01_KrusellSmith_Tutorial_CPU.ipynb, which presents a small, pedagogical CPU implementation of a Krusell-Smith economy. The notebook is designed to make the core ideas of the paper transparent.

For the full method and richer quantitative applications, please see the paper on arXiv.

Citation

If you use this notebook or the paper in your work, please cite:

@article{azinovic_yang_zemlicka_2025_sequence_space,
  title = {Deep Learning in the Sequence Space},
  author = {Azinovic-Yang, Marlon and {\v Z}emli{\v c}ka, Jan},
  year = {2025},
  journal = {arXiv preprint arXiv:2509.13623},
  url = {https://arxiv.org/abs/2509.13623}
}