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Machine learning optimization for hybrid electric vehicle charging in renewable microgrids | Scientific Reports
Nature
Renewable microgrids enhance security, reliability, and power quality in power systems by integrating solar and wind sources, reducing greenhouse gas...
2 weeks ago
Accelerating the design of lattice structures using machine learning | Scientific Reports
Nature
Lattices remain an attractive class of structures due to their design versatility; however, rapidly designing lattice structures with tailored or optimal...
2 weeks ago
Meet OmniPred: A Machine Learning Framework to Transform Experimental Design with Universal Regression Models
MarkTechPost
The ability to predict outcomes from a myriad of parameters has traditionally been anchored in specific, narrowly focused regression methods.
4 months ago
Uncertainty driven active learning of coarse grained free energy models | npj Computational Materials
Nature
Coarse graining techniques play an essential role in accelerating molecular simulations of systems with large length and time scales.
5 months ago
Bayesian reconstruction of magnetic resonance images using Gaussian processes | Scientific Reports
Nature
A central goal of modern magnetic resonance imaging (MRI) is to reduce the time required to produce high-quality images. Efforts have included hardware and...
11 months ago
Active learning for prediction of tensile properties for material extrusion additive manufacturing | Scientific Reports
Nature
Machine learning techniques were used to predict tensile properties of material extrusion-based additively manufactured parts made with Technomelt PA 6910,...
11 months ago
nnSVG for the scalable identification of spatially variable genes using nearest-neighbor Gaussian processes
Nature
Feature selection to identify spatially variable genes or other biologically informative genes is a key step during analyses of spatially-resolved...
11 months ago
A semi-empirical approach to calibrate simulation models for semiconductor devices | Scientific Reports
Nature
Semiconductor device optimization using computer-based prototyping techniques like simulation or machine learning digital twins can be time and resource...
12 months ago
Pareto optimization with small data by learning across common objective spaces | Scientific Reports
Nature
In multi-objective optimization, it becomes prohibitively difficult to cover the Pareto front (PF) as the number of points scales exponentially with the...
13 months ago
Bayesian optimization with active learning of design constraints using an entropy-based approach | npj Computational ...
Nature
The design of alloys for use in gas turbine engine blades is a complex task that involves balancing multiple objectives and constraints.
15 months ago