Variance_Reduced_Replica_Exchange_Stochastic_Gradient_MCMC：通过减少方...
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Variance_Reduced_Replica_Exchange_Stochastic_Gradient_MCMC-main.zip （56个子文件） 
Variance_Reduced_Replica_Exchange_Stochastic_Gradient_MCMC-main 
trainer.py 8KB .gitignore 113B bayes_cnn.py 4KB output cifar100_resnet20_batch_256_lr_2e-6_T_0.001_cycle_5_burn_0.7_seed_24439_74.40 116KB cifar100_resnet20_batch_256_chain_2_T_0.0003_LRgap_0.66_Tgap_0.2_F_5e6_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_adapt_c_1_seed_58476 0B cifar100_resnet20_batch_256_chain_2_T_0.0003_LRgap_0.66_Tgap_0.2_F_5e6_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_adapt_c_0_seed_31604 7KB cifar100_resnet20_batch_256_chain_2_T_0.003_LRgap_0.66_Tgap_0.2_F_5e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_adapt_c_0_seed_47841 7KB cifar100_resnet20_batch_256_chain_2_T_0.003_LRgap_0.66_Tgap_0.2_F_5e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_adapt_c_1_seed_5056 0B cifar100_resnet20_batch_256_chain_2_T_0.01_LRgap_0.66_Tgap_0.2_F_1.5e5_VR_0_p_2_burn_0.6_alpha_0.3_cycle_1_seed_47211_74.43 157KB cifar100_resnet20_batch_256_chain_1_T_1e-300_seed_67154_71.81 66KB cifar100_resnet20_batch_256_lr_2e-6_T_0.001_cycle_5_burn_0.7_seed_37225_74.08 116KB cifar100_resnet20_batch_256_lr_2e-6_T_0.001_cycle_5_burn_0.7_seed_82929_74.34 116KB cifar100_resnet20_batch_256_chain_2_T_0.003_LRgap_0.66_Tgap_0.2_F_5e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_adapt_c_1_seed_1682 0B cifar100_resnet20_batch_256_chain_1_T_1e-300_seed_81391_71.68 66KB cifar100_resnet20_batch_256_chain_2_T_0.0001_LRgap_0.66_Tgap_0.2_F_1.5e7_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_adapt_c_0_seed_27443 7KB cifar100_resnet20_batch_256_chain_2_T_0.01_LRgap_0.66_Tgap_0.2_F_1.5e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_18803_74.78 303KB cifar100_resnet32_batch_256_chain_2_T_0.01_LRgap_0.66_Tgap_0.2_F_1.5e5_VR_0_p_2_burn_0.6_alpha_0.3_cycle_1_seed_35902_76.86 167KB cifar100_resnet32_batch_256_lr_2e-6_T_0.001_cycle_5_burn_0.7_seed_79580_76.42 116KB cifar100_resnet20_batch_256_chain_2_T_0.01_LRgap_0.66_Tgap_0.2_F_1.5e5_VR_0_p_2_burn_0.6_alpha_0.3_cycle_1_seed_29292_73.06 156KB cifar100_resnet20_batch_256_chain_1_T_1e-300_seed_64760_72.19 66KB cifar100_resnet32_batch_256_chain_2_T_0.01_LRgap_0.66_Tgap_0.2_F_1.5e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_72638_77.19 293KB cifar100_resnet32_batch_256_chain_2_T_0.01_LRgap_0.66_Tgap_0.2_F_1.5e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_87124_77.54 309KB trial_1 cifar100_resnet20_batch_256_chain_2_T_0.0001_LRgap_0.66_Tgap_0.2_F_1e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_416 82KB cifar100_resnet20_batch_256_chain_2_T_0.0003_LRgap_0.66_Tgap_0.2_F_1.5e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_86549 97KB cifar100_resnet20_batch_256_chain_2_T_0.0001_LRgap_0.66_Tgap_0.2_F_1e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_92302 96KB cifar100_resnet20_batch_256_chain_2_T_0.0001_LRgap_0.66_Tgap_0.2_F_1.5e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_34759 81KB cifar100_resnet20_batch_256_chain_2_T_0.0003_LRgap_0.66_Tgap_0.2_F_1.5e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_17593 96KB cifar100_resnet20_batch_256_chain_2_T_0.0001_LRgap_0.66_Tgap_0.2_F_1.5e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_89053 152KB cifar100_resnet20_batch_256_chain_2_T_0.001_LRgap_0.66_Tgap_0.2_F_1e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_99062 126KB cifar100_resnet20_batch_256_chain_2_T_0.0003_LRgap_0.66_Tgap_0.2_F_1.5e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_83464 126KB cifar100_resnet20_batch_256_chain_2_T_0.0001_LRgap_0.66_Tgap_0.2_F_1.5e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_99973 107KB cifar100_resnet20_batch_256_chain_2_T_0.0003_LRgap_0.66_Tgap_0.2_F_1e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_34179 97KB cifar100_resnet20_batch_256_chain_2_T_0.001_LRgap_0.66_Tgap_0.2_F_1.5e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_89770 96KB cifar100_resnet20_batch_256_chain_2_T_0.001_LRgap_0.66_Tgap_0.2_F_1.5e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_31653 81KB cifar100_resnet20_batch_256_chain_2_T_0.0003_LRgap_0.66_Tgap_0.2_F_1e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_92294 96KB cifar100_resnet20_batch_256_chain_2_T_0.0003_LRgap_0.66_Tgap_0.2_F_1.5e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_38155 110KB cifar100_resnet32_batch_256_chain_2_T_0.01_LRgap_0.66_Tgap_0.2_F_1.5e5_VR_0_p_2_burn_0.6_alpha_0.3_cycle_1_seed_45730_76.05 167KB cifar100_resnet20_batch_256_chain_2_T_0.0003_LRgap_0.66_Tgap_0.2_F_5e6_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_adapt_c_1_seed_31965 9KB cifar100_resnet20_batch_256_chain_2_T_0.0001_LRgap_0.66_Tgap_0.2_F_1.5e7_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_adapt_c_1_seed_97873 1KB run.log 0B cifar100_resnet20_batch_256_chain_2_T_0.01_LRgap_0.66_Tgap_0.2_F_1.5e5_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_seed_85674_75.17 315KB cifar100_resnet20_batch_256_chain_2_T_0.001_LRgap_0.66_Tgap_0.2_F_1.5e6_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_adapt_c_1_seed_32983 9KB cifar100_resnet32_batch_256_lr_2e-6_T_0.001_cycle_5_burn_0.7_seed_84935_76.91 116KB cifar100_resnet20_batch_256_chain_2_T_0.0001_LRgap_0.66_Tgap_0.2_F_1.5e7_VR_1_p_2_burn_0.6_alpha_0.3_cycle_1_adapt_c_1_seed_69699 0B sgmcmc.py 2KB models cifar __init__.py 62B resnet.py 4KB __init__.py 0B tools transforms.py 2KB __init__.py 61B .bak neural_network.py 6KB neural_network.pyc 7KB torch_tools.py 3KB data_manipulation.py 5KB README.md 2KB grid_search.py 893B资源评论
