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  • J.E. Castrillon-Candas, D. Liu and M. Kon. Stochastic functional analysis with applications to robust machine learning. Submitted to NeurIPS. (2021).
  • J.E. Castrillon-Candas, F. Nobile and R.F.  Tempone. A hybrid collocation-perturbation approach for PDEs with random domains. Adv Comput Math 47, 40 (2021).
  • J. E. Castrillon-Candas and J. Xu. A stochastic collocation approach for parabolic PDEs with random11domain deformations.Computers & Mathematics with Applications, 93:32–49, 2021.
  • Xiaoyu Wang, Wenrui Li, Yuetian Sun, Snezana Milanovic, Mark Kon and Julio E. Castrillón- Candás. Multi-level Kriging for Large Dataset Imputation. Annals of applied statistics, under review, 2021.
  • J. E. Castrillón-Candás. High dimensional multilevel Kriging: A computational mathematics approach. , SIAM Journal of Uncertainty Quantification. under review, 2021.
  • J. E. Castrillon-Candas and Mark Kon, Analytic regularity and stochastic collocation of high dimensional Newton iterates. Advances in Computational Mathematics, 46(3):42, May 2020.
  • J.E. Castrillon-Candas, M.G Genton, R. Yokota. Multi-Level Restricted Maximum Likelihood Covariance Estimation and
    Kriging for Large Non-Gridded Spatial Datasets
    Spatial Statistics. 2016, 18, 105-124 Link
  • J.E. Castrillon-Candas. A sparse grid collocation method for parabolic PDEs with random domain deformations. Arxiv, 2017,  (Link)
  • J.E. Castrillon-Candas, F. Nobile, R. Tempone. Analytic regularityand collocation approximation for PDEs with random domaindeformations. Computers and Mathematics withApplications.  Volume 71, Issue 6, March 2016, Pages 1173–1197 (Link)

  • J.E. Castrillon-Candas, J. Li, V. Eijkhout. A Discrete AdaptedHierarchical Basis Solver For Radial Basis Function Interpolation.BIT Numerical Mathematics March 2013, Volume 53, Issue 1, pp 57-86.(Link)

  • J. E. Castrillon-Candas, V.K. Siddavanahalli, C. Bajaj. Nonequispaced Fourier Transforms for Protein-Protein Docking.ICES Technical Report, October 2005 (Link)

  • S.D. Heedene, K. Amaratunga and J. E. Castrillon-Candas, GeneralizedHierarchical Bases: a Wavelet-Ritz-Galerkin Framework for LagrangianFEM. Engineering Computations.22,1,15-37,2005 (Link)

  • C. Bajaj, J. E. Castrillon-Candas, Vinay Siddavanahalli and ZaiqingXu, Compression of Macromolecular Structures and Properties,Special Issue of Macromolecular Assemblies Highlighted, Structure,13,3, 463-471, (2005) (Link)

  • C. Bajaj, J. E. Castrillon-Candas, Vinay Siddavanahalli and ZaiqingXu, Hierarchical Compressed Volumetric Representations ofMolecular Structures, ICES TechnicalReport (Link).

  • J. E. Castrillon-Candas and K. Amaratunga, Spatially AdaptedMultiwavelets and Sparse Representation of Integral Equations onGeneral Geometries. SIAM Journal onScientific Computing, 24, 5, 1530-1566,(2003).(Link)

  • J. E. Castrillon-Candas and K. Amaratunga, Fast Computation ofContinuous Karhunen-Loeve Eigenfunctions using Wavelets,IEEE Transactions on Signal Processing, 50,1, 78-86, January 2002.(Link)

  • K. Amaratunga and J. E. Castrillon-Candas: Surface Wavelets: AMultiresolution Signal Processing Tool for 3D ComputationalModeling. International Journal forNumerical Methods in Engineering,(Link)
    52,3, 239-271, September 2001.