| Quantum Algorithm Implementations for Beginners J Abhijith, A Adedoyin, J Ambrosiano, P Anisimov, A Bärtschi, W Casper, ... ACM Transactions on Quantum Computing 3 (4), 2643-6809, 2022 | 337* | 2022 |
| Interaction screening: Efficient and sample-optimal learning of Ising models M Vuffray, S Misra, A Lokhov, M Chertkov Advances in neural information processing systems 29, 2016 | 139 | 2016 |
| Stationary solutions of the Schrödinger-Newton model---an ODE approach P Choquard, J Stubbe, M Vuffray Differential and Integral Equations 21 (7-8), 665-679, 2008 | 104 | 2008 |
| Optimal structure and parameter learning of Ising models AY Lokhov, M Vuffray, S Misra, M Chertkov Science advances 4 (3), e1700791, 2018 | 103 | 2018 |
| Approaching the rate-distortion limit with spatial coupling, belief propagation, and decimation V Aref, N Macris, M Vuffray IEEE Transactions on Information Theory 61 (7), 3954-3979, 2015 | 50 | 2015 |
| Monotonicity of dissipative flow networks renders robust maximum profit problem tractable: General analysis and application to natural gas flows M Vuffray, S Misra, M Chertkov 2015 54th IEEE conference on decision and control (CDC), 4571-4578, 2015 | 45* | 2015 |
| On the emerging potential of quantum annealing hardware for combinatorial optimization B Tasseff, T Albash, Z Morrell, M Vuffray, AY Lokhov, S Misra, C Coffrin Journal of Heuristics 30 (5), 325-358, 2024 | 37 | 2024 |
| Lossy source coding via spatially coupled LDGM ensembles V Aref, N Macris, R Urbanke, M Vuffray 2012 IEEE International Symposium on Information Theory Proceedings, 373-377, 2012 | 33 | 2012 |
| Real-time anomaly detection and classification in streaming PMU data C Hannon, D Deka, D Jin, M Vuffray, AY Lokhov 2021 IEEE Madrid PowerTech, 1-6, 2021 | 31 | 2021 |
| Efficient polynomial chaos expansion for uncertainty quantification in power systems D Métivier, M Vuffray, S Misra Electric Power Systems Research 189, 106791, 2020 | 31 | 2020 |
| Information theoretic optimal learning of gaussian graphical models S Misra, M Vuffray, AY Lokhov Conference on Learning Theory, 2888-2909, 2020 | 30* | 2020 |
| Efficient learning of discrete graphical models M Vuffray, S Misra, AY Lokhov Journal of Statistical Mechanics: Theory and Experiment 2021 (12), 124017, 2022 | 28 | 2022 |
| Graphical models for optimal power flow K Dvijotham, M Chertkov, P Van Hentenryck, M Vuffray, S Misra Constraints 22, 24-49, 2017 | 28 | 2017 |
| Online learning of power transmission dynamics AY Lokhov, M Vuffray, D Shemetov, D Deka, M Chertkov 2018 Power Systems Computation Conference (PSCC), 1-7, 2018 | 25 | 2018 |
| Programmable quantum annealers as noisy gibbs samplers M Vuffray, C Coffrin, YA Kharkov, AY Lokhov PRX Quantum 3 (2), 020317, 2022 | 24 | 2022 |
| Monotonicity properties of physical network flows and application to robust optimal allocation S Misra, M Vuffray, A Zlotnik Proceedings of the IEEE 108 (9), 1558-1579, 2020 | 24 | 2020 |
| High-quality thermal Gibbs sampling with quantum annealing hardware J Nelson, M Vuffray, AY Lokhov, T Albash, C Coffrin Physical Review Applied 17 (4), 044046, 2022 | 23 | 2022 |
| The impacts of convex piecewise linear cost formulations on AC optimal power flow C Coffrin, B Knueven, J Holzer, M Vuffray Electric Power Systems Research 199, 107191, 2021 | 23 | 2021 |
| Monotonicity of actuated flows on dissipative transport networks A Zlotnik, S Misra, M Vuffray, M Chertkov 2016 European Control Conference (ECC), 831-836, 2016 | 20 | 2016 |
| The potential of quantum annealing for rapid solution structure identification Y Pang, C Coffrin, AY Lokhov, M Vuffray Constraints 26 (1), 1-25, 2021 | 18 | 2021 |
Andrey LokhovLos Alamos National Laboratory, Theoretical DivisionVerified email at lanl.gov
