1 to 10 of 18 Results
Sep 27, 2023 -
Reproduction Code for: On Reducing the Amount of Samples Required for Training of QNNs
Python Source Code - 2.3 KB -
MD5: 3092220f87583ca17e7cfd73fdacafef
Experiments for training QNNs using training data of varying Schmidt rank. |
Sep 27, 2023 -
Reproduction Code for: On Reducing the Amount of Samples Required for Training of QNNs
Python Source Code - 1.5 KB -
MD5: ff77e11ba2a65fbf30afe3680e7903e6
Cost function and training routines procedures for PyTorch QNN simulation. |
Sep 27, 2023 -
Reproduction Code for: On Reducing the Amount of Samples Required for Training of QNNs
Python Source Code - 3.8 KB -
MD5: b0b7ff540bb8e1b631cff61a652b06f7
Configuration structures for experiments. |
Sep 27, 2023 -
Reproduction Code for: On Reducing the Amount of Samples Required for Training of QNNs
Python Source Code - 273 B -
MD5: b1a0c53c5525b9980bb82bf3784e3c7a
Various functions to modify the loss function after evaluation. |
Sep 27, 2023 -
Reproduction Code for: On Reducing the Amount of Samples Required for Training of QNNs
Python Source Code - 18.5 KB -
MD5: ee5babfdaf1828206a38944c1f26c713
QNN ansatz implementations for classical simulation using PyTorch. |
Sep 27, 2023 -
Reproduction Code for: On Reducing the Amount of Samples Required for Training of QNNs
Python Source Code - 14.4 KB -
MD5: 05a60d0e08fe086be30c1982b88ee9a8
Data generation routines for the experiments. |
Sep 27, 2023 -
Reproduction Code for: On Reducing the Amount of Samples Required for Training of QNNs
Python Source Code - 13.2 KB -
MD5: 27ae2978ce34969769e840b21da5526c
Experiment entry point. Generates training data, calls simulation and training routines and saves results. Also responsible for distributing experiment workloads to multiple processors. |
Sep 27, 2023 -
Reproduction Code for: On Reducing the Amount of Samples Required for Training of QNNs
Python Source Code - 4.6 KB -
MD5: 7cad64b10f13aa99ad9bec3335e7a72a
Logging utilities |
Sep 27, 2023 -
Reproduction Code for: On Reducing the Amount of Samples Required for Training of QNNs
Python Source Code - 826 B -
MD5: dc804c83ce2807ae1ab4dd51b1c87148
Functions for evaluating the quantum risk |
Sep 27, 2023 -
Reproduction Code for: On Reducing the Amount of Samples Required for Training of QNNs
Python Source Code - 2.2 KB -
MD5: 6bafb223195f04e5747c244b074eda3e
Experiments for training QNNs using linearly dependent data. |