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In the statistical study of Hamiltonian PDEs out of the equilibrium (lack of invariant measures), it is a natural question to understand the transport properties for canonical Gaussian measures. The f...
We investigate the frame set of regular multivariate Gaussian Gabor frames using methods from Kahler geometry such as Hormander's $\dbar$-L2 estimate with singular weight, Demailly's Calabi--Yau metho...
The classical Minkowski problem, which asks for the characterization of surface area measure in Euclidean space with Lebesgue measure, largely motivated the development of elliptic PDEs throughout the...
Conventional inferential methods for (deep) Gaussian Processes models can suffer from high computational complexity as they require large-scale operations with kernel matrices for training and inferen...
Partial differential equations (PDEs) have become an essential tool for modeling complex physical systems. Such equations are typically solved numerically via mesh-based methods, such as the finite el...
Surrogate modeling based on Gaussian processes (GPs) has received increasing attention in the analysis of complex problems in science and engineering. Despite extensive studies on GP modeling, the dev...
In this talk, we will first introduce a class of Gaussian processes, and prove the quasi-invariant theorem with respect to the Gaussian Wiener measure, which is the law of the associated Gaussian proc...
In this talk, we will show several results for correlated nearest neighbor site percolation on Z^d. In particular, we will show that in three dimensions the strongly correlated massless harmonic cryst...
In this talk, we prove that Bernoulli percolation on graph undergoes a non-trivial phase transition if the graph has bounded degrees and random walk on the graph has a heat kernel with rapid decay. Th...
In this lecture, I will discuss some of the recent progresses in the level-set percolation of Gaussian free field in (d\geq 3), including the positivity of threshold and (if time permits) sharp phase ...
In this lecture, I will discuss some of the recent progresses in the level-set percolation of Gaussian free field in (d\geq 3), including the positivity of threshold and (if time permits) sharp phase ...
The (discrete) Gaussian free field (dGFF) on a transient graph, simply put, is the random Gaussian field with covariance given through Green’s function of the random walk on that graph. It is in many ...
2022年6月17日下午,国家级人才称号获得者,清华大学殷柳国教授来中北大学信息与通信工程学院作“Generalized Sparse Codes for Non-Gaussian Channels: Code Design,Algorithms, and Applications”专题报告。本次专题报告是南邮80周年校庆之际通信与信息工程学院举办的第10次“通院学术大讲堂”校庆系列报告会。本次报...
The arbitrary-centered discrete Gaussian sampler is a fundamental subroutine in implementing lattice trapdoor sampling algorithms. However, existing approaches typically rely on either a fast implemen...
In this paper we present a practical protocol for secure ridge regression. We develop the necessary secure linear algebra tools, using only basic arithmetic over prime fields. In particular, we will s...

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