Faculty

Institution

Unit

Venue

Yun Yang

Adjunct Associate Professor

University of Illinois Urbana-Champaign

Affiliations

College of Liberal Arts & Sciences

Department of Statistics

Yun Yang is currently serving as a College Of Liberal Arts & Sciences Adjunct Associate Professor at University of Illinois Urbana-Champaign.

Honors

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Experiences

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Education

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Yun Yang

University of Illinois Urbana-Champaign

Adjunct Associate Professor

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statistical inference statistics computational statistics data science statistical methodology applied mathematics bayesian analysis machine learning mathematical optimization high-dimensional statistics machine learning research statistical models applied statistics computer science bayesian inference high-dimensional method inference bayesian statistics model selection computational optimization bayesian hierarchical modeling convex analysis approximate bayesian computation estimation theory uncertainty quantification kernel methods unsupervised machine learning numerical algorithms statistical learning theory generative models image representation knowledge discovery gaussian process reproducing kernel methods kernel ridge regression markov chain monte carlo dimensionality reduction semi-nonparametric estimation nonparametric regression posterior distribution manifold learning parameter estimation minimax rate vehicular technology mobility ensemble algorithms variational inequalities principal component analysis random matrix regularization (mathematics) on-demand transport sequential monte carlo generative ai bayesian econometrics communication-efficient surrogate communication-efficient surrogate likelihood randomized sketches bayes risk bayesian posterior distributions distributed algorithm exponential rate true clustering structure hanson-wright inequality implicit regularization exact recovery bayesian framework cultural heritage machine vision logistics management infrastructure engineering decision tree learning decision trees gaussian analysis scene analysis feature detection image classification non-parametric statistics

Notable Scholarly Works

Notable Federal Grants

Collaborators

On the Convergence of Coordinate Ascent Variational Inference. The Annals of Statistics (2025)

Anirban BhattacharyaDebdeep PatiYun Yang

statistical inferenceinferencemachine learningvariational analysisapplied mathematicsmathematical optimizationcomputational statistics

Adaptivity of Diffusion Models to Manifold Structures. Proceedings of Machine Learning Research (2024)

Yun Yang

diffusion-based modelingmanifold modelingstatistical mechanicsgeometric analysisdiffusion processdiffusionstatistical physicsmathematical sciencesapplied mathematicsmathematicsmanifold structuresdifferential geometrygeometric topology

Bayesian Model Selection via Mean-Field Variational Approximation. Journal of the Royal Statistical Society Series B (Statistical Methodology) (2024)

Yangfan ZhangYun Yang

bayesian model selectionmodel selectionstatisticsinferencestatistical inferencestatistical methodologybiostatisticsbayesian frameworkbayesian analysisevidence lower boundstatistical modelsapproximate bayesian computationbayesian inferencebayesian statistics

Wasserstein Proximal Coordinate Gradient Algorithms. arXiv (Cornell University) (2024)

Yao, RentianChen, XiaohuiYang, Yun

approximation theoryapplied mathematicsmathematical programmingmathematical optimizationconvex optimizationcomputational sciencenumerical algorithmscomputational optimizationconvex analysismathematicsnumerical analysisconvex potential energycomputational mathematicsenergy minimizationconvex self-interactionvariational analysisapproximation bayesian computationglobal optimizationlarge-scale global optimizationderivative-free optimization

A Gromov--Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening. arXiv (Cornell University) (2023)

Chen, YifanYao, RentianYang, YunChen, Jie

graph analysismachine learninggraph coarseninggraph theoryspectral theorydata sciencegraph processinggraph signal processinggraph spectrummachine learning researchapplied mathematicsconvex analysisspectrum-preserving graph coarsening

Estimating Distributions With Low-Dimensional Structures Using Mixtures of Generative Models. arXiv (Cornell University) (2023)

Tang, RongYang, Yun

statistical inferenceparameter sharingmanifold modelingmachine learningunknown submanifoldsdata sciencemanifold learninggenerative modelsmachine learning researchimage representation

Minimax Nonparametric Two-Sample Test Under Adversarial Losses. Artificial Intelligence and Statistics Conference (AISTATS) (2023)

Yun Yang

statistical inferencestatisticsstatistical methodologymachine learningadversarial machine learningmathematical optimizationadversarial losses

Minimax Rate of Distribution Estimation on Unknown Submanifolds Under Adversarial Losses. The Annals of Statistics (2023)

Rong TangYun Yang

deep learningstatistical inferencedistribution estimationmachine learningminimax rateunknown submanifolddata sciencegenerative modelsmachine learning researchgenerative aiimage representation

Minimizing Convex Functionals Over Space of Probability Measures via Kl Divergence Gradient Flow. arXiv (Cornell University) (2023)

Yao, RentianHuang, LinjunYang, Yun

statistical inferencecomputer sciencestochastic optimizationhigh-dimensional statisticskl divergencebayesian analysisconvex functionalsnumerical methodcomputational optimizationapplied mathematicsconvex analysismathematical optimizationconvex optimizationcomputational statistics

Model-Based Statistical Depth With Applications to Functional Data. Journal of nonparametric statistics (2023)

Weilong ZhaoZishen XuYue MuYun YangWei Wu

statistical inferencestatisticsdensity estimationscientific datastatistical methodologystatistical depthnonparametric statisticsdata sciencegenerative modelsmodel-based statistical depthfunctional data analysisdata modelingstatistical modelsapplied statisticscomputational statistics

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Yun Yang

Adjunct Associate Professor

University of Illinois Urbana-Champaign

Affiliations

College of Liberal Arts & Sciences

Department of Statistics

Yun Yang is currently serving as a College Of Liberal Arts & Sciences Adjunct Associate Professor at University of Illinois Urbana-Champaign.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Yun Yang

University of Illinois Urbana-Champaign

Adjunct Associate Professor

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

On the Convergence of Coordinate Ascent Variational Inference. The Annals of Statistics (2025)

Anirban BhattacharyaDebdeep PatiYun Yang

statistical inferenceinferencemachine learningvariational analysisapplied mathematicsmathematical optimizationcomputational statistics

Adaptivity of Diffusion Models to Manifold Structures. Proceedings of Machine Learning Research (2024)

Yun Yang

Bayesian Model Selection via Mean-Field Variational Approximation. Journal of the Royal Statistical Society Series B (Statistical Methodology) (2024)

Yangfan ZhangYun Yang

Wasserstein Proximal Coordinate Gradient Algorithms. arXiv (Cornell University) (2024)

Yao, RentianChen, XiaohuiYang, Yun

A Gromov--Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening. arXiv (Cornell University) (2023)

Chen, YifanYao, RentianYang, YunChen, Jie

Estimating Distributions With Low-Dimensional Structures Using Mixtures of Generative Models. arXiv (Cornell University) (2023)

Tang, RongYang, Yun

statistical inferenceparameter sharingmanifold modelingmachine learningunknown submanifoldsdata sciencemanifold learninggenerative modelsmachine learning researchimage representation

Minimax Nonparametric Two-Sample Test Under Adversarial Losses. Artificial Intelligence and Statistics Conference (AISTATS) (2023)

Yun Yang

statistical inferencestatisticsstatistical methodologymachine learningadversarial machine learningmathematical optimizationadversarial losses

Minimax Rate of Distribution Estimation on Unknown Submanifolds Under Adversarial Losses. The Annals of Statistics (2023)

Rong TangYun Yang

deep learningstatistical inferencedistribution estimationmachine learningminimax rateunknown submanifolddata sciencegenerative modelsmachine learning researchgenerative aiimage representation

Minimizing Convex Functionals Over Space of Probability Measures via Kl Divergence Gradient Flow. arXiv (Cornell University) (2023)

Yao, RentianHuang, LinjunYang, Yun

Model-Based Statistical Depth With Applications to Functional Data. Journal of nonparametric statistics (2023)

Weilong ZhaoZishen XuYue MuYun YangWei Wu

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Similar Faculty Members

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Institution

University of Illinois Urbana-Champaign

statistical inference

data mining

Marten H. Wegkamp

Institution

Cornell University

high-dimensional statistics

high dimensional statistics

Florentina Bunea

Institution

Cornell University

mixture modeling

latent space estimation

Kevin Moon

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dimensionality reduction

multidisciplinary ai

Kengo Kato

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econometric model

econometrics

Han Liu

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machine learning

applied mathematics

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pattern recognition

computational intelligence

Chris Tsokos

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ecological modelling

David Matteson

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geographical information science

spatial analysis