Andrey Y. Lokhov

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 39

Top Topics

Power Transmission

Partial Observations

Quantum Computing

Top Venues

Constraints An Int. J.

Publications

Mateusz Wilinski, Andrey Y. Lokhov
Learning of networked spreading models from noisy and incomplete data. CoRR (2024)
Andrew Chio, Russell Bent, Andrey Y. Lokhov, Jian Peng, Nalini Venkatasubramanian
Physics-based Pollutant Source Identification in Stormwater Systems. ECC (2024)
Abhijith Jayakumar, Stefano Chessa, Carleton Coffrin, Andrey Y. Lokhov, Marc Vuffray, Sidhant Misra
General Algorithms for SPAM Noise Characterization. QCE (2023)
Abhijith Jayakumar, Marc Vuffray, Andrey Y. Lokhov
Learning Energy-Based Representations of Quantum Many-Body States. CoRR (2023)
Melvyn Tyloo, Marc Vuffray, Andrey Y. Lokhov
Forced oscillation source localization from generator measurements. CoRR (2023)
Adrien Suau, Jon Nelson, Marc Vuffray, Andrey Y. Lokhov, Lukasz Cincio, Carleton Coffrin
Single-Qubit Cross Platform Comparison of Quantum Computing Hardware. QCE (2023)
Adrien Suau, Marc Vuffray, Andrey Y. Lokhov, Lukasz Cincio, Carleton Coffrin
Vector Field Visualization of Single-Qubit State Tomography. QCE (2022)
Yuchen Pang, Carleton Coffrin, Andrey Y. Lokhov, Marc Vuffray
The potential of quantum annealing for rapid solution structure identification. Constraints An Int. J. 26 (1) (2021)
Arkopal Dutt, Andrey Y. Lokhov, Marc Vuffray, Sidhant Misra
Exponential Reduction in Sample Complexity with Learning of Ising Model Dynamics. CoRR (2021)
Christopher X. Ren, Sidhant Misra, Marc Vuffray, Andrey Y. Lokhov
Learning Continuous Exponential Families Beyond Gaussian. CoRR (2021)
Jon Nelson, Marc Vuffray, Andrey Y. Lokhov, Carleton Coffrin
Single-Qubit Fidelity Assessment of Quantum Annealing Hardware. CoRR (2021)
Mateusz Wilinski, Andrey Y. Lokhov
Prediction-Centric Learning of Independent Cascade Dynamics from Partial Observations. ICML (2021)
Arkopal Dutt, Andrey Y. Lokhov, Marc Vuffray, Sidhant Misra
Exponential Reduction in Sample Complexity with Learning of Ising Model Dynamics. ICML (2021)
Yuchen Pang, Carleton Coffrin, Andrey Y. Lokhov, Marc Vuffray
Correction to: The potential of quantum annealing for rapid solution structure identification. Constraints An Int. J. 26 (1) (2021)
Jon Nelson, Marc Vuffray, Andrey Y. Lokhov, Tameem Albash, Carleton Coffrin
High-quality Thermal Gibbs Sampling with Quantum Annealing Hardware. CoRR (2021)
Abhijith Jayakumar, Andrey Y. Lokhov, Sidhant Misra, Marc Vuffray
Learning of Discrete Graphical Models with Neural Networks. CoRR (2020)
Risul Islam, Andrey Y. Lokhov, Nathan Lemons, Michalis Faloutsos
Mobility Map Inference from Thermal Modeling of a Building. CoRR (2020)
Marc Vuffray, Sidhant Misra, Andrey Y. Lokhov
Efficient Learning of Discrete Graphical Models. NeurIPS (2020)
Sidhant Misra, Marc Vuffray, Andrey Y. Lokhov
Information Theoretic Optimal Learning of Gaussian Graphical Models. COLT (2020)
Abhijith Jayakumar, Andrey Y. Lokhov, Sidhant Misra, Marc Vuffray
Learning of Discrete Graphical Models with Neural Networks. NeurIPS (2020)
Mateusz Wilinski, Andrey Y. Lokhov
Scalable Learning of Independent Cascade Dynamics from Partial Observations. CoRR (2020)
Marc Vuffray, Carleton Coffrin, Yaroslav A. Kharkov, Andrey Y. Lokhov
Programmable Quantum Annealers as Noisy Gibbs Samplers. CoRR (2020)
Marc Vuffray, Sidhant Misra, Andrey Y. Lokhov
Efficient Learning of Discrete Graphical Models. CoRR (2019)
Andrey Y. Lokhov, David Saad
Scalable Influence Estimation Without Sampling. CoRR (2019)
Andrey Y. Lokhov, Deepjyoti Deka, Marc Vuffray, Michael Chertkov
Uncovering Power Transmission Dynamic Model from Incomplete PMU Observations. CDC (2018)
Patrick J. Coles, Stephan J. Eidenbenz, Scott Pakin, Adetokunbo Adedoyin, John Ambrosiano, Petr M. Anisimov, William Casper, Gopinath Chennupati, Carleton Coffrin, Hristo N. Djidjev, David Gunter, Satish Karra, Nathan Lemons, Shizeng Lin, Andrey Y. Lokhov, Alexander Malyzhenkov, David Dennis Lee Mascarenas, Susan M. Mniszewski, Balu Nadiga, Dan O'Malley, Diane Oyen, Lakshman Prasad, Randy Roberts, Philip Romero, Nandakishore Santhi, Nikolai Sinitsyn, Pieter Swart, Marc Vuffray, Jim Wendelberger, Boram Yoon, Richard J. Zamora, Wei Zhu
Quantum Algorithm Implementations for Beginners. CoRR (2018)
Deepjyoti Deka, Armin Zare, Andrey Y. Lokhov, Mihailo R. Jovanovic, Michael Chertkov
State and noise covariance estimation in power grids using limited nodal PMUs. GlobalSIP (2017)
Andrey Y. Lokhov, David Saad
Optimal deployment of resources for maximizing impact in spreading processes. Proc. Natl. Acad. Sci. USA 114 (39) (2017)
Andrey Y. Lokhov, Marc Vuffray, Dmitry Shemetov, Deepjyoti Deka, Michael Chertkov
Online Learning of Power Transmission Dynamics. CoRR (2017)
Sidhant Misra, Marc Vuffray, Andrey Y. Lokhov, Michael Chertkov
Towards Optimal Sparse Inverse Covariance Selection through Non-Convex Optimization. CoRR (2017)
Emma M. Stewart, Philip Top, Michael Chertkov, Deepjyoti Deka, Scott Backhaus, Andrey Y. Lokhov, Ciaran M. Roberts, Val Hendrix, Sean Peisert, Anthony Florita, Thomas J. King, Matthew J. Reno
Integrated multi-scale data analytics and machine learning for the distribution grid. SmartGridComm (2017)
Andrey Y. Lokhov, Nathan Lemons, Thomas C. McAndrew, Aric A. Hagberg, Scott Backhaus
Detection of Cyber-Physical Faults and Intrusions from Physical Correlations. ICDM Workshops (2016)
Marc Vuffray, Sidhant Misra, Andrey Y. Lokhov, Michael Chertkov
Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models. NIPS (2016)
Andrey Y. Lokhov
Reconstructing parameters of spreading models from partial observations. CoRR (2016)
Andrey Y. Lokhov, Nathan Lemons, Thomas C. McAndrew, Aric A. Hagberg, Scott Backhaus
Detection of faults and intrusions in cyber-physical systems from physical correlations. CoRR (2016)
Andrey Y. Lokhov
Reconstructing Parameters of Spreading Models from Partial Observations. NIPS (2016)
Marc Vuffray, Sidhant Misra, Andrey Y. Lokhov, Michael Chertkov
Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models. CoRR (2016)
Andrey Y. Lokhov, Marc Vuffray, Sidhant Misra, Michael Chertkov
Optimal structure and parameter learning of Ising models. CoRR (2016)
Andrey Y. Lokhov, David Saad
Optimal Deployment of Resources for Maximizing Impact in Spreading Processes. CoRR (2016)
Andrey Y. Lokhov, Theodor Misiakiewicz
Efficient reconstruction of transmission probabilities in a spreading process from partial observations. CoRR (2015)
Andrey Y. Lokhov, Marc Mézard, Lenka Zdeborová
Dynamic message-passing equations for models with unidirectional dynamics. CoRR (2014)
Andrey Y. Lokhov, Marc Mézard, Hiroki Ohta, Lenka Zdeborová
Inferring the origin of an epidemy with dynamic message-passing algorithm CoRR (2013)