Selected Publications

Machine Learning

  • Efficient Learning of Discrete Graphical Models
    M. Vuffray, S. Misra, A.Y. Lokhov
    arXiv, 2019, [arXiv]

  • Information Theoretic Optimal Learning of Gaussian Graphical Models
    S. Misra, M. Vuffray, A.Y. Lokhov
    arXiv, 2019, [arXiv]

  • Optimal Structure and Parameter Learning of Ising Models
    A.Y. Lokhov, M. Vuffray, S. Misra, M. Chertkov
    Science Advances, 2018, [online], [arXiv]

  • Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models
    M. Vuffray, S. Misra, A.Y. Lokhov, M. Chertkov
    Advances in Neural Information Processing Systems (NeurIPS), 2016, [online], [arXiv]

Energy Networks

  • Uncovering Power Transmission Dynamic Model from Incomplete PMU Observations
    A.Y. Lokhov, D. Deka, M. Vuffray, M. Chertkov
    IEEE Conference on Decision and Control (CDC), 2018, [online]

  • Online Learning of Power Transmission Dynamics
    A.Y. Lokhov, M. Vuffray, D. Shemetov, D. Deka, M. Chertkov
    Power Systems Computation Conference (PSCC), 2018, [online], [arXiv]

  • Graphical Models for Optimal Power Flow
    K. Dvijotham, M. Chertkov, P. Van Hentenryck, M. Vuffray, S. Misra
    Constraints, 2017, [online], [arXiv]

  • 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
    IEEE Conference on Decision and Control (CDC), 2015, [online], [arXiv]

Information Theory

  • The Bethe Free Energy Allows to Compute the Conditional Entropy of Graphical Code Instances: A Proof From the Polymer Expansion
    N. Macris, M. Vuffray
    IEEE Transactions on Information Theory, 2016, [online], [arXiv]

  • Approaching the Rate-Distortion Limit with Spatial Coupling, Belief Propagation, and Decimation
    V. Aref, N. Macris, M. Vuffray
    IEEE Transactions on Information Theory, 2015, [online], [arXiv]

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