凹槽 发表于 2025-3-27 00:50:26
Demonstration of the Model Performance on the Benchmark Problems,ce plot of the network predictions allows the attainment of a deeper understanding of the training process. For the double-well problem, the prediction performance of the DSM network is compared with different alternative approaches, and is found to achieve results comparable to those of the best alMEET 发表于 2025-3-27 02:13:07
http://reply.papertrans.cn/67/6638/663714/663714_32.png天气 发表于 2025-3-27 06:09:13
http://reply.papertrans.cn/67/6638/663714/663714_33.png争吵 发表于 2025-3-27 11:29:43
http://reply.papertrans.cn/67/6638/663714/663714_34.png盖他为秘密 发表于 2025-3-27 17:28:57
A simple Bayesian regularisation scheme, mode of their posterior distribution. Conjugate priors for the various network parameters are introduced, which give rise to regularisation terms that can be viewed as a generalisation of simple weight decay. It is shown how the posterior mode can be found with a slightly modified version of the EMfreight 发表于 2025-3-27 19:11:14
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http://reply.papertrans.cn/67/6638/663714/663714_37.png我不明白 发表于 2025-3-28 02:33:33
http://reply.papertrans.cn/67/6638/663714/663714_38.pngEntirety 发表于 2025-3-28 10:07:53
Network Committees and Weighting Schemes,cation or by simple averaging in regression, but one can also use a weighted combination of the networks. The first section of this chapter summarises the main ideas of a recent study by Krogh and Vedelsby on network committees for simple interpolation tasks. The generalisation performance of the co搬运工 发表于 2025-3-28 11:17:58
Demonstration: Committees of Networks Trained with Different Regularisation Schemes,on performance on the regularisation method and the weighting scheme is studied. For a single-model predictor, application of the Bayesian evidence scheme is found to lead to superior results. However, when using network committees, under-regularisation can be advantageous, since it leads to a large