D. Smékal

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom D. Smékal trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. S. van Buuren
  2. Tianqi Chen

Papers from D. Smékal's perspective

Ordered by how strongly the researchers D. Smékal trusts endorse each paper. Same corpus, a different order for every researcher.

  1. XGBoost: A Scalable Tree Boosting System
  2. Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data (JAMA Internal Medicine)
  3. MICE: Multivariate Imputation by Chained Equations in R
  4. Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): The TRIPOD Statement
  5. Emergency department triage prediction of clinical outcomes using machine learning models (Critical Care)
  6. Regression Shrinkage and Selection via the Lasso
  7. The Elements of Statistical Learning
  8. Regression Modeling Strategies (Technometrics)
  9. A weakly informative default prior distribution for logistic and other regression models
  10. Regularization Paths for Generalized Linear Models via Coordinate Descent

Their papers