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The role of morphometric characteristics in predicting 20-meter sprint performance through machine learning
Nature
The aim of this study was to test the morphometric features affecting 20-m sprint performance in children at the first level of primary...
2 weeks ago
Modelling chemical processes in explicit solvents with machine learning potentials
Nature
Solvent effects influence all stages of the chemical processes, modulating the stability of intermediates and transition states,...
1 week 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
Nature
Coarse graining techniques play an essential role in accelerating molecular simulations of systems with large length and time scales.
6 months ago
Champion-level drone racing using deep reinforcement learning
Nature
First-person view (FPV) drone racing is a televised sport in which professional competitors pilot high-speed aircraft through a 3D circuit.
11 months ago
Deep Bayesian Gaussian processes for uncertainty estimation in electronic health records
Nature
One major impediment to the wider use of deep learning for clinical decision making is the difficulty of assigning a level of confidence to...
33 months ago
Stochastic learning and extremal-field map based autonomous guidance of low-thrust spacecraft
Nature
A supervised stochastic learning method called the Gaussian Process Regression (GPR) is used to design an autonomous guidance law for...
21 months ago
Mechanical behavior predictions of additively manufactured microstructures using functional Gaussian process surrogates | npj Computational Materials
Nature
Relational linkages connecting process, structure, and properties are some of the most sought after goals in additive manufacturing (AM).
37 months ago
Uncertainty-aware mixed-variable machine learning for materials design
Nature
Data-driven design shows the promise of accelerating materials discovery but is challenging due to the prohibitive cost of searching the...
20 months ago
Machine learning optimization for hybrid electric vehicle charging in renewable microgrids
Nature
Renewable microgrids enhance security, reliability, and power quality in power systems by integrating solar and wind sources,...
1 month ago