Composition-based predictions for chemically novel, high-temperature superconductors.
Training a GAN using superconductivity data
A research paper detailing the model building process of principal component regression using mathematical notation and a demonstration using the superconductivity dataset from the UCI machine learning repository.
This app allows the users to predict the super conductivity and composition of compounds.
Trabalho semestral de Redes Neurais: prevendo temperaturas criticas de supercondutores usando rede neural do tipo MLP (Multi Layer Perceptron). Trabalho feito pelos alunas Alice Barbarino Santos, Maria Eduarda de Oliveira Crist e o aluno Bruno Ferreira Brischi. Disciplina da Ilum - Escola de Ciência, ministrada por Daniel Cassar
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