Andrey Y. Lokhov

51 papers A* 5Misc 3Journal 36Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Computationally sufficient statistics for Ising models. CoRR Abhijith Jayakumar, Shreya Shukla, Marc Vuffray, Andrey Y. Lokhov, Sidhant Misra
2026	J	`jnl`	Discrete Diffusion with Sample-Efficient Estimators for Conditionals. CoRR Karthik Elamvazhuthi, Abhijith Jayakumar, Andrey Y. Lokhov
2026	J	`jnl`	Selecting Optimal Variable Order in Autoregressive Ising Models. CoRR Shiba Biswal, Marc Vuffray, Andrey Y. Lokhov
2025	J	`jnl`	Efficient Learning of Lattice Gauge Theories with Fermions. CoRR Shreya Shukla, Yukari Yamauchi, Andrey Y. Lokhov, Scott Lawrence, Abhijith Jayakumar
2025	J	`jnl`	Symmetric Linear Dynamical Systems are Learnable from Few Observations. CoRR Minh Vu, Andrey Y. Lokhov, Marc Vuffray
2024	J	`jnl`	Discrete distributions are learnable from metastable samples. CoRR Abhijith Jayakumar, Andrey Y. Lokhov, Sidhant Misra, Marc Vuffray
2024	J	`jnl`	Learning of networked spreading models from noisy and incomplete data. CoRR Mateusz Wilinski, Andrey Y. Lokhov
2024	J	`jnl`	On the emerging potential of quantum annealing hardware for combinatorial optimization. J. Heuristics Byron Tasseff, Tameem Albash, Zachary Morrell, Marc Vuffray, Andrey Y. Lokhov, Sidhant Misra, Carleton Coffrin
2024	—	`conf`	Physics-based Pollutant Source Identification in Stormwater Systems. ECC Andrew Chio, Russell Bent, Andrey Y. Lokhov, Jian Peng, Nalini Venkatasubramanian
2024	J	`jnl`	Universal framework for simultaneous tomography of quantum states and SPAM noise. Quantum Abhijith Jayakumar, Stefano Chessa, Carleton Coffrin, Andrey Y. Lokhov, Marc Vuffray, Sidhant Misra
2023	J	`jnl`	Forced oscillation source localization from generator measurements. CoRR Melvyn Tyloo, Marc Vuffray, Andrey Y. Lokhov
2023	Misc	`conf`	General Algorithms for SPAM Noise Characterization. QCE Abhijith Jayakumar, Stefano Chessa, Carleton Coffrin, Andrey Y. Lokhov, Marc Vuffray, Sidhant Misra
2023	J	`jnl`	Learning Energy-Based Representations of Quantum Many-Body States. CoRR Abhijith Jayakumar, Marc Vuffray, Andrey Y. Lokhov
2023	Misc	`conf`	Single-Qubit Cross Platform Comparison of Quantum Computing Hardware. QCE Adrien Suau, Jon Nelson, Marc Vuffray, Andrey Y. Lokhov, Lukasz Cincio, Carleton Coffrin
2022	J	`jnl`	Quantum Algorithm Implementations for Beginners. ACM Trans. Quantum Comput. Abhijith Jayakumar, Adetokunbo Adedoyin, John Ambrosiano, Petr M. Anisimov, William Casper, Gopinath Chennupati, Carleton Coffrin, Hristo N. Djidjev, David Gunter, Satish Karra, Nathan Lemons, Shizeng Lin, Alexander Malyzhenkov, David Mascarenas, Susan M. Mniszewski, Balu Nadiga, Daniel O'Malley, Diane Oyen, Scott Pakin, Lakshman Prasad, Randy Roberts, Phillip Romero, Nandakishore Santhi, Nikolai Sinitsyn, Pieter J. Swart, James G. Wendelberger, Boram Yoon, Richard J. Zamora, Wei Zhu, Stephan J. Eidenbenz, Andreas Bärtschi, Patrick J. Coles, Marc Vuffray, Andrey Y. Lokhov
2022	Misc	`conf`	Vector Field Visualization of Single-Qubit State Tomography. QCE Adrien Suau, Marc Vuffray, Andrey Y. Lokhov, Lukasz Cincio, Carleton Coffrin
2021	J	`jnl`	Correction to: The potential of quantum annealing for rapid solution structure identification. Constraints An Int. J. Yuchen Pang, Carleton Coffrin, Andrey Y. Lokhov, Marc Vuffray
2021	A*	`conf`	Exponential Reduction in Sample Complexity with Learning of Ising Model Dynamics. ICML Arkopal Dutt, Andrey Y. Lokhov, Marc Vuffray, Sidhant Misra
2021	J	`jnl`	Exponential Reduction in Sample Complexity with Learning of Ising Model Dynamics. CoRR Arkopal Dutt, Andrey Y. Lokhov, Marc Vuffray, Sidhant Misra
2021	J	`jnl`	High-quality Thermal Gibbs Sampling with Quantum Annealing Hardware. CoRR Jon Nelson, Marc Vuffray, Andrey Y. Lokhov, Tameem Albash, Carleton Coffrin
2021	J	`jnl`	Learning Continuous Exponential Families Beyond Gaussian. CoRR Christopher X. Ren, Sidhant Misra, Marc Vuffray, Andrey Y. Lokhov
2021	A*	`conf`	Prediction-Centric Learning of Independent Cascade Dynamics from Partial Observations. ICML Mateusz Wilinski, Andrey Y. Lokhov
2021	J	`jnl`	Single-Qubit Fidelity Assessment of Quantum Annealing Hardware. CoRR Jon Nelson, Marc Vuffray, Andrey Y. Lokhov, Carleton Coffrin
2021	J	`jnl`	The potential of quantum annealing for rapid solution structure identification. Constraints An Int. J. Yuchen Pang, Carleton Coffrin, Andrey Y. Lokhov, Marc Vuffray
2020	A*	`conf`	Efficient Learning of Discrete Graphical Models. NeurIPS Marc Vuffray, Sidhant Misra, Andrey Y. Lokhov
2020	A*	`conf`	Information Theoretic Optimal Learning of Gaussian Graphical Models. COLT Sidhant Misra, Marc Vuffray, Andrey Y. Lokhov
2020	A*	`conf`	Learning of Discrete Graphical Models with Neural Networks. NeurIPS Abhijith Jayakumar, Andrey Y. Lokhov, Sidhant Misra, Marc Vuffray
2020	J	`jnl`	Learning of Discrete Graphical Models with Neural Networks. CoRR Abhijith Jayakumar, Andrey Y. Lokhov, Sidhant Misra, Marc Vuffray
2020	J	`jnl`	Mobility Map Inference from Thermal Modeling of a Building. CoRR Risul Islam, Andrey Y. Lokhov, Nathan Lemons, Michalis Faloutsos
2020	J	`jnl`	Programmable Quantum Annealers as Noisy Gibbs Samplers. CoRR Marc Vuffray, Carleton Coffrin, Yaroslav A. Kharkov, Andrey Y. Lokhov
2020	J	`jnl`	Scalable Learning of Independent Cascade Dynamics from Partial Observations. CoRR Mateusz Wilinski, Andrey Y. Lokhov
2019	J	`jnl`	Efficient Learning of Discrete Graphical Models. CoRR Marc Vuffray, Sidhant Misra, Andrey Y. Lokhov
2019	J	`jnl`	Scalable Influence Estimation Without Sampling. CoRR Andrey Y. Lokhov, David Saad
2018	J	`jnl`	Quantum Algorithm Implementations for Beginners. CoRR 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 Mascarenas, Susan M. Mniszewski, Balu Nadiga, Dan O'Malley, Diane Oyen, Lakshman Prasad, Randy Roberts, Philip Romero, Nandakishore Santhi, Nikolai Sinitsyn, Pieter J. Swart, Marc Vuffray, Jim Wendelberger, Boram Yoon, Richard J. Zamora, Wei Zhu
2018	—	`conf`	Uncovering Power Transmission Dynamic Model from Incomplete PMU Observations. CDC Andrey Y. Lokhov, Deepjyoti Deka, Marc Vuffray, Michael Chertkov
2017	—	`conf`	Integrated multi-scale data analytics and machine learning for the distribution grid. SmartGridComm 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
2017	J	`jnl`	Online Learning of Power Transmission Dynamics. CoRR Andrey Y. Lokhov, Marc Vuffray, Dmitry Shemetov, Deepjyoti Deka, Michael Chertkov
2017	J	`jnl`	Optimal deployment of resources for maximizing impact in spreading processes. Proc. Natl. Acad. Sci. USA Andrey Y. Lokhov, David Saad
2017	—	`conf`	State and noise covariance estimation in power grids using limited nodal PMUs. GlobalSIP Deepjyoti Deka, Armin Zare, Andrey Y. Lokhov, Mihailo R. Jovanovic, Michael Chertkov
2017	J	`jnl`	Towards Optimal Sparse Inverse Covariance Selection through Non-Convex Optimization. CoRR Sidhant Misra, Marc Vuffray, Andrey Y. Lokhov, Michael Chertkov
2016	—	`conf`	Detection of Cyber-Physical Faults and Intrusions from Physical Correlations. ICDM Workshops Andrey Y. Lokhov, Nathan Lemons, Thomas C. McAndrew, Aric A. Hagberg, Scott Backhaus
2016	J	`jnl`	Detection of faults and intrusions in cyber-physical systems from physical correlations. CoRR Andrey Y. Lokhov, Nathan Lemons, Thomas C. McAndrew, Aric A. Hagberg, Scott Backhaus
2016	—	`conf`	Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models. NIPS Marc Vuffray, Sidhant Misra, Andrey Y. Lokhov, Michael Chertkov
2016	J	`jnl`	Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models. CoRR Marc Vuffray, Sidhant Misra, Andrey Y. Lokhov, Michael Chertkov
2016	J	`jnl`	Optimal Deployment of Resources for Maximizing Impact in Spreading Processes. CoRR Andrey Y. Lokhov, David Saad
2016	J	`jnl`	Optimal structure and parameter learning of Ising models. CoRR Andrey Y. Lokhov, Marc Vuffray, Sidhant Misra, Michael Chertkov
2016	—	`conf`	Reconstructing Parameters of Spreading Models from Partial Observations. NIPS Andrey Y. Lokhov
2016	J	`jnl`	Reconstructing parameters of spreading models from partial observations. CoRR Andrey Y. Lokhov
2015	J	`jnl`	Efficient reconstruction of transmission probabilities in a spreading process from partial observations. CoRR Andrey Y. Lokhov, Theodor Misiakiewicz
2014	J	`jnl`	Dynamic message-passing equations for models with unidirectional dynamics. CoRR Andrey Y. Lokhov, Marc Mézard, Lenka Zdeborová
2013	J	`jnl`	Inferring the origin of an epidemy with dynamic message-passing algorithm CoRR Andrey Y. Lokhov, Marc Mézard, Hiroki Ohta, Lenka Zdeborová