NOTICE

causal-perception-implementation
Copyright (c) 2026 José M. Álvarez

This is the research code accompanying a paper on causal perception (the
comparison of competing structural causal models through the lens of
interventional and counterfactual distributions). The copyright is held by
the author(s) of the paper.

This open-source release is distributed and maintained by Santander AI Lab
with the author's consent. The CI/CD, governance and security infrastructure
added for this release (files under .github/) is Copyright (c) 2026
Santander Group.

This product is licensed under the Apache License, Version 2.0 (the "License");
you may not use this product except in compliance with the License.
A copy of the License is included in the LICENSE file at the root of this
repository and is also available at:

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
License for the specific language governing permissions and limitations
under the License.

-------------------------------------------------------------------------------
Third-party data (NOT redistributed in this repository)

This repository contains code for experiments that rely on the German Credit
(Statlog) dataset. That dataset is third-party data and is NOT included or
redistributed here; it is fetched at runtime from OpenML by the data
preparation script (src/data_prep.py). See data/README.md for provenance, the
variable mapping, and citation:

  - Hofmann, H. (1994). Statlog (German Credit Data).
    UCI Machine Learning Repository. https://doi.org/10.24432/C5NC77
    Also available as OpenML dataset "credit-g" (https://www.openml.org/d/31).
  - Chiappa, S. (2019). Path-Specific Counterfactual Fairness.
    Proceedings of the AAAI Conference on Artificial Intelligence, 33(01).
    Source of the causal DAG over the German Credit variables used here.