v1.0.4

Code for the paper Quantum anomaly detection in the latent space of proton collision events at the LHC (https://arxiv.org/abs/2301.10780). The qad package associated with this work was created for reproducibility of the results and ease-of-use in future studies.

In this work, we investigate unsupervised quantum machine learning algorithms for anomaly detection tasks in particle physics data.

v1.0.3

Code for the paper Quantum anomaly detection in the latent space of proton collision events at the LHC (https://arxiv.org/abs/2301.10780). The qad package associated with this work was created for reproducibility of the results and ease-of-use in future studies.

In this work, we investigate unsupervised quantum machine learning algorithms for anomaly detection tasks in particle physics data.

v1.0.2

Complete readthedocs page, READMEs, and code structure of the qad package.

v1.0.1

Working version of the readthedocs page.

v1.0.0: Merge pull request #7 from vbelis/docs-reformat

Docs reformat

Adding one-class (Q)SVM and initial plotting code

Added unsupervised kernel machines and first version of the ROC plotting and uncertainty computation given the k-fold tests.

v0.3.0

Main skeleton for the implementation of the Autoencoder, clustering models, and kernel machines (both classical and quantum).

Full Changelog: https://github.com/QML-HEP/latent-ad-qml/commits/v.0.3.0