Andrey Y. Lokhov

Orcid: 0000-0003-3269-7263

According to our database¹, Andrey Y. Lokhov authored at least 35 papers between 2013 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

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PhD thesis

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Bibliography

2024

Learning of networked spreading models from noisy and incomplete data.

[BibT_eX]

[DOI]

Mateusz Wilinski

Andrey Y. Lokhov

CoRR, 2024

2023

Forced oscillation source localization from generator measurements.

[BibT_eX]

[DOI]

Melvyn Tyloo

Marc Vuffray

Andrey Y. Lokhov

CoRR, 2023

Learning Energy-Based Representations of Quantum Many-Body States.

[BibT_eX]

[DOI]

Abhijith Jayakumar

Marc Vuffray

Andrey Y. Lokhov

CoRR, 2023

Single-Qubit Cross Platform Comparison of Quantum Computing Hardware.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

General Algorithms for SPAM Noise Characterization.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

2022

Vector Field Visualization of Single-Qubit State Tomography.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2022

2021

High-quality Thermal Gibbs Sampling with Quantum Annealing Hardware.

[BibT_eX]

[DOI]

CoRR, 2021

Single-Qubit Fidelity Assessment of Quantum Annealing Hardware.

[BibT_eX]

[DOI]

CoRR, 2021

Learning Continuous Exponential Families Beyond Gaussian.

[BibT_eX]

[DOI]

CoRR, 2021

Correction to: The potential of quantum annealing for rapid solution structure identification.

[BibT_eX]

[DOI]

Constraints An Int. J., 2021

The potential of quantum annealing for rapid solution structure identification.

[BibT_eX]

[DOI]

Constraints An Int. J., 2021

Prediction-Centric Learning of Independent Cascade Dynamics from Partial Observations.

[BibT_eX]

[DOI]

Mateusz Wilinski

Andrey Y. Lokhov

Proceedings of the 38th International Conference on Machine Learning, 2021

Exponential Reduction in Sample Complexity with Learning of Ising Model Dynamics.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Programmable Quantum Annealers as Noisy Gibbs Samplers.

[BibT_eX]

[DOI]

CoRR, 2020

Mobility Map Inference from Thermal Modeling of a Building.

[BibT_eX]

[DOI]

CoRR, 2020

Scalable Learning of Independent Cascade Dynamics from Partial Observations.

[BibT_eX]

[DOI]

Mateusz Wilinski

Andrey Y. Lokhov

CoRR, 2020

Efficient Learning of Discrete Graphical Models.

[BibT_eX]

[DOI]

Marc Vuffray

Sidhant Misra

Andrey Y. Lokhov

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning of Discrete Graphical Models with Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Information Theoretic Optimal Learning of Gaussian Graphical Models.

[BibT_eX]

[DOI]

Sidhant Misra

Marc Vuffray

Andrey Y. Lokhov

Proceedings of the Conference on Learning Theory, 2020

2019

Scalable Influence Estimation Without Sampling.

[BibT_eX]

[DOI]

Andrey Y. Lokhov

David Saad

CoRR, 2019

2018

Quantum Algorithm Implementations for Beginners.

[BibT_eX]

[DOI]

CoRR, 2018

Uncovering Power Transmission Dynamic Model from Incomplete PMU Observations.

[BibT_eX]

[DOI]

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017

Optimal deployment of resources for maximizing impact in spreading processes.

[BibT_eX]

[DOI]

Andrey Y. Lokhov

David Saad

Proc. Natl. Acad. Sci. USA, 2017

Online Learning of Power Transmission Dynamics.

[BibT_eX]

[DOI]

CoRR, 2017

Towards Optimal Sparse Inverse Covariance Selection through Non-Convex Optimization.

[BibT_eX]

[DOI]

CoRR, 2017

Integrated multi-scale data analytics and machine learning for the distribution grid.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Smart Grid Communications, 2017

State and noise covariance estimation in power grids using limited nodal PMUs.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

2016

Optimal structure and parameter learning of Ising models.

[BibT_eX]

[DOI]

CoRR, 2016

Detection of faults and intrusions in cyber-physical systems from physical correlations.

[BibT_eX]

[DOI]

CoRR, 2016

Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Reconstructing Parameters of Spreading Models from Partial Observations.

[BibT_eX]

[DOI]

Andrey Y. Lokhov

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Detection of Cyber-Physical Faults and Intrusions from Physical Correlations.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

2015

Efficient reconstruction of transmission probabilities in a spreading process from partial observations.

[BibT_eX]

[DOI]

Andrey Y. Lokhov

Theodor Misiakiewicz

CoRR, 2015

2014

Dynamic message-passing equations for models with unidirectional dynamics.

[BibT_eX]

[DOI]

Andrey Y. Lokhov

Marc Mézard

Lenka Zdeborová

CoRR, 2014

2013

Inferring the origin of an epidemy with dynamic message-passing algorithm

[BibT_eX]

[DOI]

CoRR, 2013

Andrey Y. Lokhov

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