276 citations · 1.4k across the 34 of their papers we have counts for
34 papers
Sparse Statistical Modeling in Condensed Matter Physics
J. McGee, S. V. Dordevic
In this work we explore the possibility of using sparse statistical modeling in condensed matter physics. The procedure is employed to two well known problems: elemental supercondu…
A universal scaling of condensation temperature in quantum fluids
S. V. Dordevic
The phenomena of superconductivity and superfluidity are believed to originate from the same underlying physics, namely the condensation of either bosons or pairs of fermions (Coop…
Searching for new heavy fermions with deep learning
S. V. Dordevic
Deep learning models were developed and implemented to aid the search for new heavy fermion compounds. For the purpose of these calculations a database of more than 200 heavy fermi…
Diffusion Models for Conditional Generation of Hypothetical New Families of Superconductors
Samuel Yuan, S. V. Dordevic
Effective computational search holds great potential for aiding the discovery of High-Temperature Superconductors (HTSs), especially given the lack of systematic methods for their…
ScGAN: A Generative Adversarial Network to Predict Hypothetical Superconductors
Evan Kim, S. V. Dordevic
Despite having been discovered more than three decades ago, High Temperature Superconductors (HTSs) lack both an explanation for their mechanisms and a systematic way to search for…
Clustering Superconductors Using Unsupervised Machine Learning
B. Roter, N. Ninkovic, S. V. Dordevic
In this work we used unsupervised machine learning methods in order to find possible clustering structures in superconducting materials data sets. We used the SuperCon database, as…