40 citations · 120 across the 8 of their papers we have counts for
4 papers · 1 filter
High pressure hydrogen by machine learning and quantum Monte Carlo
Andrea Tirelli, Giacomo Tenti, Kousuke Nakano +1
We have developed a technique combining the accuracy of quantum Monte Carlo in describing the electron correlation with the efficiency of a Machine Learning Potential (MLP). We use…
Unsupervised machine learning approaches to the -state Potts model
Andrea Tirelli, Danyella O. Carvalho, Lucas A. Oliveira +3
In this paper with study phase transitions of the -state Potts model, through a number of unsupervised machine learning techniques, namely Principal Component Analysis (PCA), $k…
Application of canonical augmentation to the atomic substitution problem
Genki I. Prayogo, Andrea Tirelli, Keishu Utimula +3
A common approach for studying a solid solution or disordered system within a periodic ab-initio framework is to create a supercell in which a certain amount of target elements is…
Learning quantum phase transitions through Topological Data Analysis
Andrea Tirelli, Natanael C. Costa
We implement a computational pipeline based on a recent machine learning technique, namely the Topological Data Analysis (TDA), that has the capability of extracting powerful infor…