Quantum computing offers significant potential for tackling complex problems, yet preparing quantum states from real-world data remains a critical challenge. We introduce the statistics-informed ...
MachineShop is a meta-package for statistical and machine learning with a unified interface for model fitting, prediction, performance assessment, and presentation of results. Support is provided for ...
1 Faculty of Informatics, The University of Fukuchiyama, Kyoto, Japan. 2 School of Radiological Technology, Gunma Prefectural College of Health Sciences, Gunma, Japan. 3 School of Health Sciences, ...
Gene regulatory networks (GRNs) reveal the complex molecular interactions that govern cell state. However, it is challenging for identifying causal relations among genes due to noisy data and ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Non-Commercial (NC): Only non-commercial uses of the work are permitted. Article Views ...
In this work, the authors have demonstrated the use of machine learning (ML) models in the prediction of bulk modulus for High Entropy Alloys (HEA). For the first time, ML has been used for optimizing ...
The Scientific Computing group at CWI develops efficient mathematical methods to simulate and predict real-world phenomena with inherent uncertainties. Such uncertainties arise from e.g. uncertain ...
Regression learning is one of the long-standing problems in statistics, machine learning, and deep learning (DL). We show that writing this problem as a probabilistic expectation over (unknown) ...
Medical metal implants are required to have excellent mechanical properties and high biocompatibility to handle the complex human environment, which is a challenge that has always existed for ...
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