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Found 7 papers, 1 papers with code
Machine Learning Based Optimization Workflow for Tuning Numerical Settings of Differential Equation Solvers for Boundary Value Problems
One category of these is boundary value solvers, which are used to solve real-world problems formulated as differential equations with boundary conditions.
Machine learning-based optimization workflow of the homogeneity of spunbond nonwovens with human validation
In this paper, we present a machine learning-based optimization workflow aimed at improving the homogeneity of spunbond nonwovens.
Deep Anomaly Detection on Tennessee Eastman Process Data
Our extensive study will facilitate choosing appropriate anomaly detection methods in industrial applications.
Attribute-based Explanations of Non-Linear Embeddings of High-Dimensional Data
Embeddings of high-dimensional data are widely used to explore data, to verify analysis results, and to communicate information.
Visual Probing and Correction of Object Recognition Models with Interactive user feedback
Applications of such technologies are highly diverse ranging from natural language processing to computer vision.
Persistent Intersection Homology for the Analysis of Discrete Data
Topological data analysis is becoming increasingly relevant to support the analysis of unstructured data sets.
Topological Machine Learning with Persistence Indicator Functions
Techniques from computational topology, in particular persistent homology, are becoming increasingly relevant for data analysis.
