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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
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...
3 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...
11 months ago
A survey on Bayesian nonparametric learning for time series analysis
Frontiers
Time series analysis aims to understand underlying patterns and relationships in data to inform decision-making. As time series data are becoming more...
5 months ago
Automatic Kernel Selection for Gaussian Processes Regression with Approximate Bayesian Computation and ...
Frontiers
The current work introduces a novel combination of two Bayesian tools, Gaussian Processes (GPs), and the use of the Approximate Bayesian...
82 months ago
Stochastic learning and extremal-field map based autonomous guidance of low-thrust spacecraft | Scientific Reports
Nature
A supervised stochastic learning method called the Gaussian Process Regression (GPR) is used to design an autonomous guidance law for...
19 months ago
Learning with few samples in deep learning for image classification, a mini-review
Frontiers
Deep learning has achieved enormous success in various computer tasks. The excellent performance depends heavily on adequate training...
18 months ago
Mechanical behavior predictions of additively manufactured microstructures using functional Gaussian process ...
Nature
Relational linkages connecting process, structure, and properties are some of the most sought after goals in additive manufacturing (AM).
36 months ago
Bayesian nonparametric models characterize instantaneous strategies in a competitive dynamic game
Nature
Previous studies of strategic social interaction in game theory have predominantly used games with clearly-defined turns and limited choices...
62 months ago
Uncertainty-aware mixed-variable machine learning for materials design | Scientific Reports
Nature
Data-driven design shows the promise of accelerating materials discovery but is challenging due to the prohibitive cost of searching the...
19 months ago