August 10, 2018 article A data-driven statistical model for predicting the critical temperature of a superconductor Computational Materials Science DOI: 10.1016/j.commatsci.2018.07.052 OpenAlex Authors 0 Author list not loaded yet. Cited by 3 stored of 246 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Adaptation Using Spatially Distributed Gaussian Processes 2025 Journal of the American Statistical Association article Computer Science Gaussian Processes and Bayesian Inference Open access 0 citations Interpretably learning the critical temperature of superconductors: Electron concentration and feature dimensionality reduction 2024 APL Materials article Materials Science Machine Learning in Materials Science Open access 4 citations Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets 2020 Nature Communications article Computer Science Machine Learning in Healthcare Open access 312 citations 3 results References 0