6 citations · 10 across the 9 of their papers we have counts for
9 papers
Scalable generative modeling of non-Gaussian spatio-temporal fields via autoregressive Gaussian processes
Carrie J. Lei-Cramer, Jian Cao, Matthias Katzfuss
Generative modeling of spatio-temporal fields is crucial for a variety of applications, including stochastic weather generators and climate-model surrogates. However, many such fie…
Parallel Approximations for High-Dimensional Multivariate Normal Probability Computation in Confidence Region Detection Applications
Xiran Zhang, Sameh Abdulah, Jian Cao +4
Addressing the statistical challenge of computing the multivariate normal (MVN) probability in high dimensions holds significant potential for enhancing various applications. One c…
A Dynamics Theory of Implicit Regularization in Deep Low-Rank Matrix Factorization
Jian Cao, Chen Qian, Yihui Huang +5
Implicit regularization is an important way to interpret neural networks. Recent theory starts to explain implicit regularization with the model of deep matrix factorization (DMF)…
Locally anisotropic covariance functions on the sphere
Jian Cao, Jingjie Zhang, Zhuoer Sun +1
Rapid developments in satellite remote-sensing technology have enabled the collection of geospatial data on a global scale, hence increasing the need for covariance functions that…
Scalable Gaussian-process regression and variable selection using Vecchia approximations
Jian Cao, Joseph Guinness, Marc G. Genton +1
Gaussian process (GP) regression is a flexible, nonparametric approach to regression that naturally quantifies uncertainty. In many applications, the number of responses and covari…
Scalable computation of predictive probabilities in probit models with Gaussian process priors
Jian Cao, Daniele Durante, Marc G. Genton
Predictive models for binary data are fundamental in various fields, and the growing complexity of modern applications has motivated several flexible specifications for modeling th…
Exploiting Low Rank Covariance Structures for Computing High-Dimensional Normal and Student- Probabilities
Jian Cao, Marc G. Genton, David E. Keyes +1
We present a preconditioned Monte Carlo method for computing high-dimensional multivariate normal and Student- probabilities arising in spatial statistics. The approach combines…
Large-scale Environmental Data Science with ExaGeoStatR
Sameh Abdulah, Yuxiao Li, Jian Cao +4
Parallel computing in Gaussian process calculations becomes necessary for avoiding computational and memory restrictions associated with large-scale environmental data science appl…
O(N) Hierarchical algorithm for computing the expectations of truncated multi-variate normal distributions in N dimensions
Jingfang Huang, Fuhui Fang, George Turkiyyah +3
In this paper, we study the -dimensional integral representing the expectation of a function where is the t…