1 citations · 1 across the 3 of their papers we have counts for
4 papers
Structural Chart of Copper-Silver Nanoalloys through machine learning
Manoj Settem, Emanuele Telari, Antonio Tinti +2
Nanoalloys (or alloy nanoparticles) are an important class of materials that are promising for their functional properties. However, designing synthesis protocols to control their…
Bayesian Neural Networks versus deep ensembles for uncertainty quantification in machine learning interatomic potentials
Riccardo Farris, Emanuele Telari, Nongnuch Artrith +2
Neural-network-based machine learning interatomic potentials have emerged as powerful tools for predicting atomic energies and forces, enabling accurate and efficient simulations i…
Inherent structural descriptors via machine learning
Emanuele Telari, Antonio Tinti, Manoj Settem +10
Finding proper collective variables for complex systems and processes is one of the most challenging tasks in simulations, which limits the interpretation of experimental and simul…
Charting nanocluster structures via convolutional neural networks
Emanuele Telari, Antonio Tinti, Manoj Settem +3
A general method to obtain a representation of the structural landscape of nanoparticles in terms of a limited number of variables is proposed. The method is applied to a large dat…