2,401 to 2,410 of 2,462 Results
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". |
Adobe PDF - 158.8 KB -
MD5: e2e6fbb55a2e0cb2f2fd0c46f3086cc4
The average losses at the end of training for QNNs using training data of varying Schmidt ranks with mean Schmidt ranks in {1,2,4,64}. |
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". |
Adobe PDF - 165.4 KB -
MD5: 7591bfc8ed33637d989ac57790ccf6a4
Figure 1: The eigenvalues introduced by U†VS after training with four orthogonal inputs for a for a low-risk hypothesis (left) and for a high-risk hypothesis (right). |
Adobe PDF - 68.6 KB -
MD5: 80bc1f5e3db61210162ddf4b8ffe23d3
The average risk after training a 6-qubit QNN for randomly generated target unitaries using linearly dependent data according. For each number of training pairs t, the Schmidt rank is chosen as such that r · t = d. The lower bound for the risk for this configuration is shown as a dashed line, the expected risk according to the proposed new lower bo... |
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. |
ZIP Archive - 182.8 MB -
MD5: 8dba18ba2b5bd59caebd71d64e04c17f
Raw data (losses and risks) for training QNNs using entangled training data that is not linearly independent in H_X.
Directory t[a] contains results for QNNs trained with "a" training samples.
For analyzed results see nlihx_exp_points.npy. |
Adobe PDF - 68.7 KB -
MD5: 60f2614c7fffce46d724ccc90c2e1a10
The average risk after training a 6-qubit QNN for randomly generated target unitaries using orthogonal data. For each number of training pairs t, the Schmidt rank is chosen as such that r · t = d. The lower bound for the risk for this configuration is shown as a dashed line. The expected risk according to the proposed new lower bound is shown as a... |
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. |
ZIP Archive - 183.6 MB -
MD5: 808a025fe107f06ba43821ed90fd3036
Raw data (losses and risks) for training QNNs using orthogonal entangled training data.
Directory t[a] contains results for QNNs trained with "a" training samples.
For analyzed results see orthogonal_exp_points.npy |
