Quantum Computing @IAAS

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Software Name: Pennylane

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Data repository for "Minimial-Risk Training Samples for QNN Training from Measurements" Oct 8, 2024 Mandl, Alexander; Bechtold, Marvin; Barzen, Johanna; Leymann, Frank, 2024, "Data repository for "Minimial-Risk Training Samples for QNN Training from Measurements"", https://doi.org/10.18419/darus-4113, DaRUS, V1 Replication code and experiment result data for training Quantum Neural Networks with entangled data using one-dimensional projectors as observables. This is the version of the code that was used to generate the experiment results in the related publication. Experiments: - exp_in...
Reproduction Code for: On Reducing the Amount of Samples Required for Training of QNNs Sep 27, 2023 Mandl, Alexander; Barzen, Johanna; Leymann, Frank; Mangold, Victoria; Riegel, Benedikt; Vietz, Daniel; Winterhalter, Felix, 2023, "Reproduction Code for: On Reducing the Amount of Samples Required for Training of QNNs", https://doi.org/10.18419/darus-3445, DaRUS, V1 Replication code for training Quantum Neural Networks using entangled datasets. This is the version of the code that was used to generate the experiment results in the related publication. For future developments and discussion see the Github repository. Experiments: avg_rank_exp...
Data Repository for: On Reducing the Amount of Samples Required for Training of QNNs Sep 27, 2023 Mandl, Alexander; Barzen, Johanna; Leymann, Frank; Mangold, Victoria; Riegel, Benedikt; Vietz, Daniel; Winterhalter, Felix, 2023, "Data Repository for: On Reducing the Amount of Samples Required for Training of QNNs", https://doi.org/10.18419/darus-3442, DaRUS, V1 Simulation experiment data for training Quantum Neural Networks (QNNs) using entangled datasets. The experiments investigate the validity of the lower bounds for the expected risk after training QNNs given by the extensions to the Quantum No-Free-Lunch theorem presented in the re...

Data repository for "Minimial-Risk Training Samples for QNN Training from Measurements"

Oct 8, 2024

Mandl, Alexander; Bechtold, Marvin; Barzen, Johanna; Leymann, Frank, 2024, "Data repository for "Minimial-Risk Training Samples for QNN Training from Measurements"", https://doi.org/10.18419/darus-4113, DaRUS, V1

Replication code and experiment result data for training Quantum Neural Networks with entangled data using one-dimensional projectors as observables. This is the version of the code that was used to generate the experiment results in the related publication. Experiments: - exp_in...

Reproduction Code for: On Reducing the Amount of Samples Required for Training of QNNs

Sep 27, 2023

Mandl, Alexander; Barzen, Johanna; Leymann, Frank; Mangold, Victoria; Riegel, Benedikt; Vietz, Daniel; Winterhalter, Felix, 2023, "Reproduction Code for: On Reducing the Amount of Samples Required for Training of QNNs", https://doi.org/10.18419/darus-3445, DaRUS, V1

Replication code for training Quantum Neural Networks using entangled datasets. This is the version of the code that was used to generate the experiment results in the related publication. For future developments and discussion see the Github repository. Experiments: avg_rank_exp...

Data Repository for: On Reducing the Amount of Samples Required for Training of QNNs

Sep 27, 2023

Mandl, Alexander; Barzen, Johanna; Leymann, Frank; Mangold, Victoria; Riegel, Benedikt; Vietz, Daniel; Winterhalter, Felix, 2023, "Data Repository for: On Reducing the Amount of Samples Required for Training of QNNs", https://doi.org/10.18419/darus-3442, DaRUS, V1

Simulation experiment data for training Quantum Neural Networks (QNNs) using entangled datasets. The experiments investigate the validity of the lower bounds for the expected risk after training QNNs given by the extensions to the Quantum No-Free-Lunch theorem presented in the re...

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