five

L2LFlows: Generating High-Fidelity 3D Calorimeter Images

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NIAID Data Ecosystem2026-05-01 收录
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https://zenodo.org/record/8284809
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This upload contains the datasets used in arXiv:2302.11594. The file g4-showers_950k_10x10_train_val_test.pt contains the 760k training, 95k validation and 95k test showers as well as their incident energies. It should be loaded as follows:  - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -  import torch  list_tensors = torch.load(args.file_path) for (idx, tensor) in enumerate(list_tensors):     [showers_train, showers_val, showers_test, inc_energies_train, inc_energies_val, inc_energies_test] = list_tensors - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -  The file g4-showers_665k_10x10_test.pt contains 665k additional showers that were used for the classifier scaling studies, in addition to the 95k test showers from the file g4-showers_950k_10x10_train_val_test.pt. It should be loaded as follows:  - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -  import torch list_tensors = torch.load("g4-showers_950k_10x10_train_val_test.pt")  [showers_geant, inc_energies_geant] = list_tensors - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -  A detailed description of how the datasets were simulated can be found in the paper.
创建时间:
2023-09-18
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