Dataset: Quanutm parameter estimation with uncertainty quantification from continuous measurement data using neural network ensembles

Dataset for the paper Quantum parameter estimation with uncertainty quantification from continuous measurement data using neural network ensembles. The training and validation data used to train all models in the work are presented as .npy files for easy use with the NumPy Python library. The MLflow logs generated for each experiement presented in the paper are stored in the mlruns.zip file. To examine them using the MLflow UI ensure the MLflow package is installed, unzip the file and run the command: mlflow ui --port 5000 Each MLflow experiement run also contains a log of the random seed used to generate the noise added to the training data for full reproducibility as well as the trained models themselves. The test data is the same as the test data uploaded to https://doi.org/10.5281/zenodo.8305509.