RSF Components of the best five individuals. حسب Larasmoyo Nugroho (18078260)

"…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …"

Open loop simulation. حسب Larasmoyo Nugroho (18078260)

"…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …"

Average wind test fitness. حسب Larasmoyo Nugroho (18078260)

"…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …"

Internal process of a policy gradient block. حسب Larasmoyo Nugroho (18078260)

"…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …"

Training process of a DDPG individual. حسب Larasmoyo Nugroho (18078260)

"…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …"

PbGA search phases to find the best individuals. حسب Larasmoyo Nugroho (18078260)

"…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …"

Previous usages of DRL in solving PDG problems. حسب Larasmoyo Nugroho (18078260)

"…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …"

Internal process of a critic gradient block. حسب Larasmoyo Nugroho (18078260)

"…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …"

Best Individuals from the mapping phase. حسب Larasmoyo Nugroho (18078260)

"…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …"

Table_1_Integrated Evolutionary Learning: An Artificial Intelligence Approach to Joint Learning of Features and Hyperparameters for Optimized, Explainable Machine Learning.DOCX حسب Nina de Lacy (6559520)

"…In IEL the machine learning algorithm of choice is nested inside an evolutionary algorithm which selects features and hyperparameters over generations on the basis of an information function to converge on an optimal solution. …"

Table_2_Integrated Evolutionary Learning: An Artificial Intelligence Approach to Joint Learning of Features and Hyperparameters for Optimized, Explainable Machine Learning.DOCX حسب Nina de Lacy (6559520)

"…In IEL the machine learning algorithm of choice is nested inside an evolutionary algorithm which selects features and hyperparameters over generations on the basis of an information function to converge on an optimal solution. …"

datasheet1_Graph Neural Networks for Maximum Constraint Satisfaction.pdf حسب Jan Tönshoff (10192709)

"…We introduce a graph neural network architecture for solving such optimization problems. The architecture is generic; it works for all binary constraint satisfaction problems. …"

The_Code_for_High_Order_Analytical_Continuation حسب Jian Ma (19747060)

"…The optimal order of the analytical continuation algorithm is contingent upon the noise level of gravity data. …"

Additional information on the sequence model. حسب Jérôme Tubiana (14559981)

Low-Order Scaling <i>G</i>₀<i>W</i>₀ by Pair Atomic Density Fitting حسب Arno Förster (8356044)

"…We derive a low-scaling <i>G</i>₀<i>W</i>₀ algorithm for molecules using pair atomic density fitting (PADF) and an imaginary time representation of the Green’s function and describe its implementation in the Slater type orbital (STO)-based Amsterdam density functional (ADF) electronic structure code. …"

Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield... حسب Uttam Khatri (12689072)

"…The objective of this research was to employ efficient biomarkers for the diagnostic analysis and classification of AD based on combining structural MRI (sMRI) and resting-state functional MRI (rs-fMRI). …"

Data_Sheet_1_Multivariate Brain Functional Connectivity Through Regularized Estimators.DOCX حسب Raymond Salvador (813880)

"…<p>Functional connectivity analyses are typically based on matrices containing bivariate measures of covariability, such as correlations. …"

Data_Sheet_2_Multivariate Brain Functional Connectivity Through Regularized Estimators.DOCX حسب Raymond Salvador (813880)

"…<p>Functional connectivity analyses are typically based on matrices containing bivariate measures of covariability, such as correlations. …"

Data_Sheet_3_Multivariate Brain Functional Connectivity Through Regularized Estimators.DOCX حسب Raymond Salvador (813880)

"…<p>Functional connectivity analyses are typically based on matrices containing bivariate measures of covariability, such as correlations. …"

Metabolomic Coverage of Chemical-Group-Submetabolome Analysis: Group Classification and Four-Channel Chemical Isotope Labeling LC-MS حسب Shuang Zhao (484057)

"…We developed a computer algorithm to classify chemical structures according to their functional groups. …"