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avg_rank_losses.npy
Sep 27, 2023 - Data Repository for: On Reducing the Amount of Samples Required for Training of QNNs
Unknown - 1.0 KB - MD5: 3ab5355e889b0bdc4038631e8198b157
Map (r: int-> (t: int -> l: float)) of average final losses "l" after training of QNNs with "t" entangled datasets of average Schmidt rank "r".
avg_rank_risks.npy
Sep 27, 2023 - Data Repository for: On Reducing the Amount of Samples Required for Training of QNNs
Unknown - 618 B - MD5: 64cd3be5713e8bbe896a1234fd657aef
Map (r: int-> (t: int -> R: float)) of average final risks "R" after training of QNNs with "t" entangled datasets of average Schmidt rank "r".
nlihx_exp_points.npy
Sep 27, 2023 - Data Repository for: On Reducing the Amount of Samples Required for Training of QNNs
Unknown - 184 B - MD5: d938321dcf959b96639d9543ae6e759d
Array containing the average risks after training with t = 1,2,4,8,16,32,64 entangled training samples that are not linearly independent in H_X.
orthogonal_exp_points.npy
Sep 27, 2023 - Data Repository for: On Reducing the Amount of Samples Required for Training of QNNs
Unknown - 184 B - MD5: 7d96b191470e360b62deb994ecdf808c
Array containing the average risks after training with t = 1,2,4,8,16,32,64 orthogonal entangled training samples.
muse-small.db
Apr 28, 2021 - MUSE Datenset
Unknown - 53.6 MB - MD5: 90811fa7a42ced478a66b95bedf8b7eb
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