Data-Driven Time Series Reconstruction for Modern Power Systems Research. - Minas Chatzos; Mathieu Tanneau; Pascal Van Hentenryck (CoRR, 2021)

Learning Optimization Proxies for Large-Scale Security-Constrained Economic Dispatch. - Wenbo Chen 001; Seonho Park; Mathieu Tanneau; Pascal Van Hentenryck (CoRR, 2021)

Learning chordal extensions. - Defeng Liu; Andrea Lodi 001; Mathieu Tanneau (J. Glob. Optim., 2021)

Design and implementation of a modular interior-point solver for linear optimization. - Mathieu Tanneau; Miguel F. Anjos; Andrea Lodi 001 (Math. Program. Comput., 2021)

Risk-Aware Control and Optimization for High-Renewable Power Grids. - Neil Barry; Minas Chatzos; Wenbo Chen 001; Dahye Han; Chaofan Huang; Roshan Joseph; Michael Klamkin; Seonho Park; Mathieu Tanneau; Pascal Van Hentenryck; Shangkun Wang; Hanyu Zhang; et al. (CoRR, 2022)

Active Bucketized Learning for ACOPF Optimization Proxies. - Michael Klamkin; Mathieu Tanneau; Terrence W. K. Mak; Pascal Van Hentenryck (CoRR, 2022)

Just-In-Time Learning for Operational Risk Assessment in Power Grids. - Oliver Stover; Pranav Karve; Sankaran Mahadevan; Wenbo Chen 001; Haoruo Zhao; Mathieu Tanneau; Pascal Van Hentenryck (CoRR, 2022)

Confidence-Aware Graph Neural Networks for Learning Reliability Assessment Commitments. - Seonho Park; Wenbo Chen 001; Dahye Han; Mathieu Tanneau; Pascal Van Hentenryck (CoRR, 2022)

End-to-End Feasible Optimization Proxies for Large-Scale Economic Dispatch. - Wenbo Chen 001; Mathieu Tanneau; Pascal Van Hentenryck (CoRR, 2023)

Asset Bundling for Wind Power Forecasting. - Hanyu Zhang; Mathieu Tanneau; Chaofan Huang; V. Roshan Joseph; Shangkun Wang; Pascal Van Hentenryck (CoRR, 2023)

Strong Mixed-Integer Formulations for Transmission Expansion Planning with FACTS Devices. - Kevin Wu; Mathieu Tanneau; Pascal Van Hentenryck (CoRR, 2023)

Dual Conic Proxies for AC Optimal Power Flow. - Guancheng Qiu; Mathieu Tanneau; Pascal Van Hentenryck (CoRR, 2023)

Learning Optimal Power Flow Value Functions with Input-Convex Neural Networks. - Andrew W. Rosemberg; Mathieu Tanneau; Bruno Fanzeres; Joaquim Dias Garcia; Pascal Van Hentenryck (CoRR, 2023)

Disjunctive cuts in Mixed-Integer Conic Optimization. - Andrea Lodi 001; Mathieu Tanneau; Juan Pablo Vielma (Math. Program., 2023)

Learning Regionally Decentralized AC Optimal Power Flows With ADMM. - Terrence W. K. Mak; Minas Chatzos; Mathieu Tanneau; Pascal Van Hentenryck (IEEE Trans. Smart Grid, 2023)

Bound Tightening Using Rolling-Horizon Decomposition for Neural Network Verification. - Haoruo Zhao; Hassan L. Hijazi; Haydn Thomas Jones; Juston Moore; Mathieu Tanneau; Pascal Van Hentenryck (CPAIOR (2), 2024)

Compact Optimality Verification for Optimization Proxies. - Wenbo Chen 001; Haoruo Zhao; Mathieu Tanneau; Pascal Van Hentenryck (ICML, 2024)

Dual Lagrangian Learning for Conic Optimization. - Mathieu Tanneau; Pascal Van Hentenryck (NeurIPS, 2024)

Dual Interior-Point Optimization Learning. - Michael Klamkin; Mathieu Tanneau; Pascal Van Hentenryck (CoRR, 2024)

Scalable Exact Verification of Optimization Proxies for Large-Scale Optimal Power Flow. - Rahul Nellikkath; Mathieu Tanneau; Pascal Van Hentenryck; Spyros Chatzivasileiadis (CoRR, 2024)

Weather-Informed Probabilistic Forecasting and Scenario Generation in Power Systems. - Hanyu Zhang; Reza Zandehshahvar; Mathieu Tanneau; Pascal Van Hentenryck (CoRR, 2024)

Dual Conic Proxy for Semidefinite Relaxation of AC Optimal Power Flow. - Guancheng Qiu; Mathieu Tanneau; Pascal Van Hentenryck (CoRR, 2025)

Conformal Prediction with Upper and Lower Bound Models. - Miao Li; Michael Klamkin; Mathieu Tanneau; Reza Zandehshahvar; Pascal Van Hentenryck (CoRR, 2025)

PGLearn - An Open-Source Learning Toolkit for Optimal Power Flow. - Michael Klamkin; Mathieu Tanneau; Pascal Van Hentenryck (CoRR, 2025)