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Marc Vuffray
Marc Vuffray
Staff Research Scientist, Los Alamos National Laboratory
Verified email at lanl.gov - Homepage
Title
Cited by
Cited by
Year
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
305*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
1322016
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
1002008
Optimal structure and parameter learning of Ising models
AY Lokhov, M Vuffray, S Misra, M Chertkov
Science advances 4 (3), e1700791, 2018
992018
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
462015
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
44*2015
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
332012
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
292021
Information theoretic optimal learning of gaussian graphical models
S Misra, M Vuffray, AY Lokhov
Conference on Learning Theory, 2888-2909, 2020
29*2020
Graphical models for optimal power flow
K Dvijotham, M Chertkov, P Van Hentenryck, M Vuffray, S Misra
Constraints 22, 24-49, 2017
282017
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
arXiv preprint arXiv:2210.04291, 2022
272022
Efficient learning of discrete graphical models
M Vuffray, S Misra, AY Lokhov
Journal of Statistical Mechanics: Theory and Experiment 2021 (12), 124017, 2022
252022
Efficient polynomial chaos expansion for uncertainty quantification in power systems
D Métivier, M Vuffray, S Misra
Electric Power Systems Research 189, 106791, 2020
252020
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
242018
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
232020
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
222021
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
202022
Monotonicity of actuated flows on dissipative transport networks
A Zlotnik, S Misra, M Vuffray, M Chertkov
2016 European Control Conference (ECC), 831-836, 2016
202016
Programmable quantum annealers as noisy gibbs samplers
M Vuffray, C Coffrin, YA Kharkov, AY Lokhov
PRX Quantum 3 (2), 020317, 2022
182022
The potential of quantum annealing for rapid solution structure identification
Y Pang, C Coffrin, AY Lokhov, M Vuffray
Constraints 26 (1), 1-25, 2021
182021
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