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541 to 550 of 12,469 Results
spec.json
Apr 7, 2025 - CSI Dataset espargos-0007: Passive target with four synchronized ESPARGOS antenna arrays in a lab room
JSON - 9.6 KB - MD5: 73cd9756227b8a259048e64f93505515
Machine-readable description file
CBSD_MCMC_chain.hdf5
Mar 21, 2025 - DLC1 knockdown in EMT in MCF10A cells
Hierarchical Data Format - 122.1 MB - MD5: 452f4f6ede41fc70fcdc0184d9c3ebfc
Complete posterior samples from MCMC sampling in HDF5
CBSD_Pypesto_Parameters.hdf5
Mar 21, 2025 - DLC1 knockdown in EMT in MCF10A cells
Hierarchical Data Format - 118.4 KB - MD5: 7a5b0997d318069f5aeb7ced5d66cd10
Model calibration results in HFD5 format
CBSD_Pypesto_Parameters_optimization_dictionary.json
Mar 21, 2025 - DLC1 knockdown in EMT in MCF10A cells
JSON - 931 B - MD5: b79c3cfb6b6ab7ceda22fd319c5337db
Dictionary containing the optimized parameter values
GP_00.json
Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates.
JSON - 553.7 KB - MD5: 21610e5f675a9c616922962e836f1742
GP_01.json
Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates.
JSON - 560.3 KB - MD5: 6a5507abfa6ca21b864210f8a9a720eb
GP_02.json
Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates.
JSON - 546.2 KB - MD5: 1790b4a412ea8c0235809e20538e539f
GP_03.json
Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates.
JSON - 546.2 KB - MD5: 7a0b79d1f887ac6dd9ce1c7d75fa8b28
GP_04.json
Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates.
JSON - 555.3 KB - MD5: cce918a488a3074f5ab1ba3d0fe7b344
LHS_00.json
Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates.
JSON - 1.3 MB - MD5: a6cbae1b4477d3e08c2775ccf15d5c68
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