Scalable Gaussian processes for predicting the optical, physical, thermal, and mechanical properties of inorganic glasses with large datasets
Among machine learning approaches, Gaussian process regression (GPR) is an extremely
useful technique to predict composition–property relationships in glasses. The GPR's main …
useful technique to predict composition–property relationships in glasses. The GPR's main …
Predicting glass properties by using physics-and chemistry-informed machine learning models
Physics-and chemistry-informed machine learning (ML) models were trained by using
descriptors in the element physical and chemical properties domain, which include …
descriptors in the element physical and chemical properties domain, which include …
Xrrf: An explainable reasonably randomised forest algorithm for classification and regression problems
Tree-based ensemble algorithms (TEAs) have had a transformative impact in various fields.
However, when they are applied to real-time critical problems such as medical analysis …
However, when they are applied to real-time critical problems such as medical analysis …
Advanced Explainable Machine Learning (XML) Approaches and Their Applications in Manufacturing Processes
Q Ma - 2024 - search.proquest.com
Manufacturing is at the forefront of technological advances, and machine learning
techniques offer unprecedented opportunities for process optimization, quality improvement …
techniques offer unprecedented opportunities for process optimization, quality improvement …