The first comprehensive Lean 4 formalization of statistical learning theory, featuring Gaussian Lipschitz concentration and Dudley's entropy integral-establishes a reusable foundation for formalizing ML theory.

High-dimensional statistics with R

Thresholded Sparse CCA for Multiple Measurements

Thresholded Ordered Sparse CCA

Advanced anomaly detection using topological data analysis and manifold learning.

Covariate-varying Networks

Bayesian survival models for high-dimensional data

Python package for penalized sieve estimation in tensor product spaces for non-parametric regression and classification estimation.

End-to-end Python implementation of Ma et al.'s (2025) matrix-variate diffusion index models for macroeconomic forecasting. Features α-PCA factor extraction, supervised screening, and ILS estimation for high-dimensional forecasting with preserved structural information.

High-dimensional Mediation Testing For Highly Correlated Mediators

Generalized Decomposition Priors on R2

A systematic review on False Discovery Rates.

Structure-Adaptive Elastic Net method for high-dimensional regression with external structural information

List of software packages for repeated measures analysis in -omics data

Implementation and presentation of the Variational Sparse Coding (VSC) model. High Dimensional Statistics course project.

Presentation of the VSC model, a variant of VAE - 📔 High Dimensional Statistics

Northwestern University, Graduate Course

Implementation of High-dimensional vector autoregression time series modeling via tensor decomposition, Di Wang, Yao Zheng, Heng Lian, Guodong Li. Written in JAX.

Simulation for "Method-of-Moments Inference for GLMs and Doubly Robust Functionals under Proportional Asymptotics"

Direct Python ports of Nonlinear Matrix Factorization implementations