Chance-Constrained Optimal Covariance Steering with Iterative Risk Allocation. - Joshua Pilipovsky; Panagiotis Tsiotras (ACC, 2021)

Covariance Steering With Optimal Risk Allocation. - Joshua Pilipovsky; Panagiotis Tsiotras (IEEE Trans. Aerosp. Electron. Syst., 2021)

Distribution Steering for Discrete-Time Linear Systems with General Disturbances using Characteristic Functions. - Vignesh Sivaramakrishnan; Joshua Pilipovsky; Meeko Oishi; Panagiotis Tsiotras (ACC, 2022)

Distributionally Robust Covariance Steering with Optimal Risk Allocation. - Venkatraman Renganathan; Joshua Pilipovsky; Panagiotis Tsiotras (ACC, 2023)

Data-Driven Covariance Steering Control Design. - Joshua Pilipovsky; Panagiotis Tsiotras (CDC, 2023)

Probabilistic Verification of ReLU Neural Networks via Characteristic Functions. - Joshua Pilipovsky; Vignesh Sivaramakrishnan; Meeko Oishi; Panagiotis Tsiotras (L4DC, 2023)

Computationally Efficient Chance Constrained Covariance Control with Output Feedback. - Joshua Pilipovsky; Panagiotis Tsiotras (CDC, 2024)

Distributionally Robust Density Control with Wasserstein Ambiguity Sets. - Joshua Pilipovsky; Panagiotis Tsiotras (CDC, 2024)

Data-driven robust covariance control for uncertain linear systems. - Joshua Pilipovsky; Panagiotis Tsiotras (L4DC, 2024)

DUST: A Framework for Data-Driven Density Steering. - Joshua Pilipovsky; Panagiotis Tsiotras (CoRR, 2024)

SAVER: A Toolbox for SAmpling-Based, Probabilistic VERification of Neural Networks. - Vignesh Sivaramakrishnan; Krishna Chaitanya Kalagarla; Rosalyn A. Devonport; Joshua Pilipovsky; Panagiotis Tsiotras; Meeko Oishi (HSCC, 2025)