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.
Graded homework for the class Phsy-231 @epfl
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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