NIPS Proceedingsβ

David Eriksson

3 Papers

  • Scalable Global Optimization via Local Bayesian Optimization (2019)
  • Scaling Gaussian Process Regression with Derivatives (2018)
  • Scalable Log Determinants for Gaussian Process Kernel Learning (2017)