PUBlications
Publications by Julio Enrique Castrillon Candas
Explore scholarly works of Stochastic Mathematical Machine Learning group leader.
- Stochastic tensor space feature theory with applications to robust machine learning
- J.E. Castrillon-Candas, D. Liu, S. Yang, X. Zhang, and M. Kon
- arXiv:2110.01729
- 2025
- Spatial best linear unbiased prediction: A computational mathematics approach for high dimensional massive datasets
- J.E. Castrillon-Candas
- Advances in Computational Mathematics
- arXiv:1701.00285
- 2024
- Uncertainty quantification of receptor ligand binding sites prediction
- N. Chen, D. Yu, D. Beglov, M. Kon, J. E. Castrillón-Candás
- arXiv 2401.11312
- 2024
- Multilevel stochastic optimization for imputation in massive medical data records
- W. Li, X. Wang, Y. Sun, S. Milanovic, M. Kon and J. E. Castrillón-Candás
- IEEE Transactions on Big Data, 10, pp. 122-131
- 2024
- Uncertainty quantification and complex analyticity of the nonlinear Poisson-Boltzmann equation for the interface problem with random domains
- T. Norton, J. Xu, B. Choi, M. Kon, and J. E. Castrillón-Candás
- arXiv 2309.16439
- 2023
- Analytic regularity of strong solutions for the complexified stochastic non-linear Poisson Boltzmann Equation
- B. Choi, J. Xu, T. Norton, M. Kon, and J. E. Castrillón-Candás
- arXiv:2309.16068v1
- 2023
- Stochastic functional analysis and multilevel vector field anomaly detection
- J. E. Castrillón-Candás, M. Kon
- arXiv:2207.06229
- 2023
- Anomaly detection: A functional analysis perspective
- J. E. Castrillon-Candas and M. Kon
- Journal of Multivariate Analysis, 189, p. 104885
- 2022
- Existence of Strong Solution for the Complexified Non-linear Poisson Boltzmann Equation
- B. Choi, J. Xu, T. Norton, M. Kon, and J. E. Castrillón-Candás
- arXiv:2106.05811
- 2022
- A hybrid collocation-perturbation approach for PDEs with random domains
- J.E. Castrillon-Candas, F. Nobile and R.F. Tempone
- Advances in Computational Mathematics, 47, p. 40.
- 2021
- A stochastic collocation approach for parabolic PDEs with random domain deformations
- J. E. Castrillon-Candas and J. Xu
- Computers & Mathematics with Applications, 93:32–49
- 2021
- Analytic regularity and stochastic collocation of high dimensional Newton iterates
- J. E. Castrillon-Candas and Mark Kon
- Advances in Computational Mathematics, 46(3):42
- May 2020
- Multi-Level Restricted Maximum Likelihood Covariance Estimation and Kriging for Large Non-Gridded Spatial Datasets
- J.E. Castrillon-Candas, M.G Genton, R. Yokota
- Spatial Statistics. 2016, 18, 105-124
- 2016
- Analytic regularity and collocation approximation for PDEs with random domain deformations
- J.E. Castrillon-Candas, F. Nobile, R. Tempone
- Computers and Mathematics withApplications. Volume 71, Issue 6, Pages 1173–1197
- arXiv: 1312.7845
- March 2016
- A Discrete Adapted Hierarchical Basis Solver For Radial Basis Function Interpolation
- J.E. Castrillon-Candas, J. Li, V. Eijkhout
- BIT Numerical Mathematics, Volume 53, Issue 1, pp 57-86
- DOI: 10.1007/s10543-012-0397-x
- March 2013
- Nonequispaced Fourier Transforms for Protein-Protein Docking
- J. E. Castrillon-Candas, V.K. Siddavanahalli, C. Bajaj
- ICES Technical Report
- October 2005
- Generalized Hierarchical Bases: a Wavelet-Ritz-Galerkin Framework for Lagrangian FEM
- J. E. Castrillon-Candas and S.D. Heedene, K. Amaratunga
- Engineering Computations.22,1,15-37
- 2005
- Compression of Macromolecular Structures and Properties
- J. E. Castrillon-Candas, C. Bajaj, Vinay Siddavanahalli and ZaiqingXu
- Special Issue of Macromolecular Assemblies Highlighted, Structure,13,3, 463-471
- 2005
- Spatially Adapted Multiwavelets and Sparse Representation of Integral Equations on General Geometries
- J. E. Castrillon-Candas and K. Amaratunga
- SIAM Journal on Scientific Computing, 24, 5, 1530-1566
- DOI: 10.1137/S1064827501371238
- 2003
- Fast Computation of Continuous Karhunen-Loeve Eigenfunctions using Wavelets
- J. E. Castrillon-Candas and K. Amaratung
- IEEE Transactions on Signal Processing, 50,1, 78-86
- DOI: 10.1109/78.972484
- January 2002
- A Multiresolution Signal Processing Tool for 3D Computational Modeling
- J. E. Castrillon-Candas and K. Amaratunga
- International Journal for Numerical Methods in Engineering, 52,3, 239-271
- DOI: 10.1002/nme.238
- September 2001
CONTACT
Stochastic Machine Learning Group
- Department of Mathematics and Statistics Boston University, 665 Commonwealth Ave. Boston, MA 02215
- + (617) 353-9549
- jcandas@bu.edu
- mkon@math.bu.edu
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