| A decentralized framework for the optimal coordination of distributed energy resources MF Anjos, A Lodi, M Tanneau IEEE Transactions on Power Systems 34 (1), 349-359, 2018 | 52 | 2018 |
| Learning optimization proxies for large-scale security-constrained economic dispatch W Chen, S Park, M Tanneau, P Van Hentenryck Electric Power Systems Research 213, 108566, 2022 | 35 | 2022 |
| Learning regionally decentralized ac optimal power flows with admm TWK Mak, M Chatzos, M Tanneau, P Van Hentenryck IEEE Transactions on Smart Grid, 2023 | 15 | 2023 |
| Disjunctive cuts in mixed-integer conic optimization A Lodi, M Tanneau, JP Vielma Mathematical Programming 199 (1), 671-719, 2023 | 14 | 2023 |
| Design and implementation of a modular interior-point solver for linear optimization M Tanneau, MF Anjos, A Lodi Mathematical Programming Computation 13 (3), 509-551, 2021 | 13 | 2021 |
| End-to-End Feasible Optimization Proxies for Large-Scale Economic Dispatch W Chen, M Tanneau, P Van Hentenryck IEEE Transactions on Power Systems, 1-12, 2023 | 11 | 2023 |
| Data-driven time series reconstruction for modern power systems research M Chatzos, M Tanneau, P Van Hentenryck Electric Power Systems Research 212, 108589, 2022 | 8 | 2022 |
| Confidence-aware graph neural networks for learning reliability assessment commitments S Park, W Chen, D Han, M Tanneau, P Van Hentenryck IEEE Transactions on Power Systems, 2023 | 7 | 2023 |
| Learning chordal extensions D Liu, A Lodi, M Tanneau Journal of Global Optimization 81 (1), 3-22, 2021 | 6 | 2021 |
| Risk-aware control and optimization for high-renewable power grids N Barry, M Chatzos, W Chen, D Han, C Huang, R Joseph, M Klamkin, ... arXiv preprint arXiv:2204.00950, 2022 | 5 | 2022 |
| A linear outer approximation of line losses for DC-based optimal power flow problems H Zhao, M Tanneau, P Van Hentenryck Electric Power Systems Research 212, 108272, 2022 | 4 | 2022 |
| Bound tightening using rolling-horizon decomposition for neural network verification H Zhao, H Hijazi, H Jones, J Moore, M Tanneau, P Van Hentenryck arXiv preprint arXiv:2401.05280, 2024 | 3 | 2024 |
| Active bucketized learning for acopf optimization proxies M Klamkin, M Tanneau, TWK Mak, P Van Hentenryck arXiv preprint arXiv:2208.07497, 2022 | 3 | 2022 |
| Just-in-time learning for operational risk assessment in power grids O Stover, P Karve, S Mahadevan, W Chen, H Zhao, M Tanneau, ... arXiv preprint arXiv:2209.12762, 2022 | 2 | 2022 |
| Tulip: An open-source interior-point linear optimization solver with abstract linear algebra MF Anjos, A Lodi, M Tanneau GERAD HEC Montréal, 2019 | 2 | 2019 |
| Dual Conic Proxies for AC Optimal Power Flow G Qiu, M Tanneau, P Van Hentenryck arXiv preprint arXiv:2310.02969, 2023 | 1 | 2023 |
| Strong Mixed-Integer Formulations for Transmission Expansion Planning with FACTS Devices K Wu, M Tanneau, P Van Hentenryck arXiv preprint arXiv:2310.02347, 2023 | 1 | 2023 |
| On the benefits of stochastic economic dispatch in real-time electricity markets H Zhao, M Tanneau, P Van Hentenryck arXiv preprint arXiv:2308.06386, 2023 | 1 | 2023 |
| Dual Lagrangian Learning for Conic Optimization M Tanneau, P Van Hentenryck arXiv preprint arXiv:2402.03086, 2024 | | 2024 |
| Dual Interior-Point Optimization Learning M Klamkin, M Tanneau, P Van Hentenryck arXiv preprint arXiv:2402.02596, 2024 | | 2024 |
Pascal Van HentenryckGeorgia Institute of TechnologyVerified email at isye.gatech.edu
