Michailidis, George

19 publications

TMLR 2025 Covariate-Dependent Graphical Model Estimation via Neural Networks with Statistical Guarantees Jiahe Lin, Yikai Zhang, George Michailidis

NeurIPS 2025 Stochastic Regret Guarantees for Online Zeroth- and First-Order Bilevel Optimization Parvin Nazari, Bojian Hou, Davoud Ataee Tarzanagh, Li Shen, George Michailidis

TMLR 2024 A VAE-Based Framework for Learning Multi-Level Neural Granger-Causal Connectivity Jiahe Lin, Huitian Lei, George Michailidis

JMLR 2024 Axiomatic Effect Propagation in Structural Causal Models Raghav Singal, George Michailidis

JMLR 2024 Logistic Regression Under Network Dependence Somabha Mukherjee, Ziang Niu, Sagnik Halder, Bhaswar B. Bhattacharya, George Michailidis

JMLR 2023 Bayesian Spiked Laplacian Graphs Leo L Duan, George Michailidis, Mingzhou Ding

JMLR 2023 Inference on the Change Point Under a High Dimensional Covariance Shift Abhishek Kaul, Hongjin Zhang, Konstantinos Tsampourakis, George Michailidis

JMLR 2023 Low Tree-Rank Bayesian Vector Autoregression Models Leo L Duan, Zeyu Yuwen, George Michailidis, Zhengwu Zhang

JMLR 2022 Joint Estimation and Inference for Data Integration Problems Based on Multiple Multi-Layered Gaussian Graphical Models Subhabrata Majumdar, George Michailidis

JMLR 2022 Regularized and Smooth Double Core Tensor Factorization for Heterogeneous Data Davoud Ataee Tarzanagh, George Michailidis

ICML 2021 Flow-Based Attribution in Graphical Models: A Recursive Shapley Approach Raghav Singal, George Michailidis, Hoiyi Ng

JMLR 2020 Change Point Estimation in a Dynamic Stochastic Block Model Monika Bhattacharjee, Moulinath Banerjee, George Michailidis

JMLR 2020 Regularized Estimation of High-Dimensional Factor-Augmented Vector Autoregressive (FAVAR) Models Jiahe Lin, George Michailidis

JMLR 2017 Regularized Estimation and Testing for High-Dimensional Multi-Block Vector-Autoregressive Models Jiahe Lin, George Michailidis

JMLR 2016 Joint Structural Estimation of Multiple Graphical Models Jing Ma, George Michailidis

JMLR 2016 Penalized Maximum Likelihood Estimation of Multi-Layered Gaussian Graphical Models Jiahe Lin, Sumanta Basu, Moulinath Banerjee, George Michailidis

JMLR 2015 Network Granger Causality with Inherent Grouping Structure Sumanta Basu, Ali Shojaie, George Michailidis

MLJ 2015 Operator-Valued Kernel-Based Vector Autoregressive Models for Network Inference Néhémy Lim, Florence d'Alché-Buc, Cédric Auliac, George Michailidis

NeurIPS 2010 Penalized Principal Component Regression on Graphs for Analysis of Subnetworks Ali Shojaie, George Michailidis