Parameters setting for the Adam optimizer using the popular deep learning libraries.</p
<p>Table of simulation, network and optimization parameters for the ND artificial network model.</p
Parameters and their associated values used in model setup and scenario runs.</p
<p>Parameter settings used in the simulations (units for all rates are “per gene per generation”).</...
The objective of this research is to evaluate the effects of Adam when used together with a wide and...
<p>List of the built-in optimization parameters used by the Genome Partitioner algorithm.</p
<p>Main parameter settings of the evolutionary wavelet neural networks for the different datasets.</...
<p>Parameters of the different approaches algorithms depending on the computational budget.</p
<p>The parameters of the public tools used in RNAMiner, the parameter values, and the descriptions.<...
Final parameter settings of quantification systems A, B, and C after parameter optimization.</p
<p>Mode of the parameter settings identified as optimal in bootstrap samples.</p
Performance of SVM models on NIPT prediction using different parameter setting.</p
Results from parameter optimisation for HC-CNN with various activation functions and learning rates....
<p>Main set of parameters used for the DNA model and for the numerical simulations.</p
<p>Parameter values in deterministic and probabilistic sensitivity analysis (SA).</p
Hybrid inverse planning and optimization (HIPO) algorithm optimization parameters.</p
<p>Table of simulation, network and optimization parameters for the ND artificial network model.</p
Parameters and their associated values used in model setup and scenario runs.</p
<p>Parameter settings used in the simulations (units for all rates are “per gene per generation”).</...
The objective of this research is to evaluate the effects of Adam when used together with a wide and...
<p>List of the built-in optimization parameters used by the Genome Partitioner algorithm.</p
<p>Main parameter settings of the evolutionary wavelet neural networks for the different datasets.</...
<p>Parameters of the different approaches algorithms depending on the computational budget.</p
<p>The parameters of the public tools used in RNAMiner, the parameter values, and the descriptions.<...
Final parameter settings of quantification systems A, B, and C after parameter optimization.</p
<p>Mode of the parameter settings identified as optimal in bootstrap samples.</p
Performance of SVM models on NIPT prediction using different parameter setting.</p
Results from parameter optimisation for HC-CNN with various activation functions and learning rates....
<p>Main set of parameters used for the DNA model and for the numerical simulations.</p
<p>Parameter values in deterministic and probabilistic sensitivity analysis (SA).</p
Hybrid inverse planning and optimization (HIPO) algorithm optimization parameters.</p
<p>Table of simulation, network and optimization parameters for the ND artificial network model.</p
Parameters and their associated values used in model setup and scenario runs.</p
<p>Parameter settings used in the simulations (units for all rates are “per gene per generation”).</...
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