Statistical Learning and Graphical Models
Christopher X. Ren, Sidhant Misra, Marc Vuffray, Andrey Y. Lokhov Short description: Introducing a new estimator ISODUS for continuous nonGaussian exponential family distributions with unbounded support and multibody interactions

Arkopal Dutt, Andrey Y. Lokhov, Marc Vuffray, Sidhant Misra, Short description: Learning of graphical models from correlated samples in the outofequilibrium regime is exponentially easier compared to the independent samples setting

Abhijith J., Andrey Y. Lokhov, Sidhant Misra, Marc Vuffray Short description: Discovering parsimonious basis representation with NeurISE, an Interaction Screening based estimator incorporating neural networks acting as universal energy function approximators

Marc Vuffray, Sidhant Misra, Andrey Y. Lokhov Short description: Learning discrete graphical models with arbitrary alphabets and multibody interactions using GRISE, Generalized Regularized Interaction Screening Estimator

Sidhant Misra, Marc Vuffray, Andrey Y. Lokhov Short description: Beyond LASSO with SLICE and DICE algorithms that achieve the IT bound on sample complexity for learning the structure of Gaussian graphical models 
Andrey Y. Lokhov, Marc Vuffray, Sidhant Misra, Michael Chertkov Marc Vuffray, Sidhant Misra, Andrey Y. Lokhov, Michael Chertkov Short description: Sampleoptimal “Interaction Screening” method for provably learning arbitrary binary graphical models without any assumptions 
Dynamic MessagePassing
Mateusz Wilinski, Andrey Y. Lokhov Short description: Introducing a scalable algorithm SLICER that estimates parameters of the Independent Cascade model. In the context of learning for inference, tractable inference from the learned model generates a better prediction of marginal probabilities compared to the original model 
Andrey Y. Lokhov, David Saad Short description: Scalable dynamic messagepassing algorithm for estimation of spread in the Independent Cascade type diffusion models 
Hanlin Sun, David Saad, Andrey Y. Lokhov Short description: Exact dynamic messagepassing equations for estimation of marginal infection probabilities for collaborative and mutually exclusive epidemics, and their use for the optimal resource allocation problem 
Andrey Y. Lokhov, David Saad Short description: Optimal targeting in spreading processes with dynamic messagepassing equations and forwardbackward optimization method used in artificial neural networks 
Andrey Y. Lokhov Andrey Y. Lokhov, Theodor Misiakiewicz Short description: Introducing a dynamic messagepassing algorithm DMPrec for learning parameters of spreading models from partial observations 
Andrey Y. Lokhov, Marc Mézard, Lenka Zdeborová Short description: Solution of many dynamic models (random field Ising model, epidemic and rumor spreading, threshold models) on given network instances 
Andrey Y. Lokhov, Marc Mézard, Hiroki Ohta, Lenka Zdeborová Short description: Localization of the epidemic source from a partial snapshot at unknown time 
Quantum Computing
Marc Vuffray, Carleton Coffrin, Yaroslav Kharkov, Andrey Y. Lokhov Short description: Characterization of quantum annealers’ sampling properties using statistical learning methods, including unexpected spurious interactions in the output distribution due to qubit noise 
Jon Nelson, Marc Vuffray, Andrey Y. Lokhov, Carleton Coffrin Short description: Developing a protocol for quantifying the error performance of individual qubits in quantum annealing computers

Quantum Algorithm Implementations for Beginners Short description: An introduction to quantum computing algorithms and their implementation on IBM QX quantum computer

Short description: Identification of a hard instance of an optimization problem where quantum annealing provides notable performance gains over established classical algorithms 
Dynamical Systems, Power Grid, and CyberPhysical Systems
Zheguang Zhao, Deepjyoti Deka, Andrey Y. Lokhov Short description: Learning of an effective cyberphysical model from discrete and continuous time series of physical and control processes 
Jordan Snyder, Anatoly Zlotnik, Andrey Y. Lokhov Short description: Learning of macroscopic reducedorder models in systems of coupled oscillators from coarsegrained microscopic data

Christopher Hannon, Deepjyoti Deka, Dong Jin, Marc Vuffray, Andrey Y. Lokhov Short description: Anomaly detection and classification in streaming phasor measurement units data via realtime learning of effective dynamical model 
Andrey Y. Lokhov, Marc Vuffray, Dmitry Shemetov, Deepjyoti Deka, Michael Chertkov Online Learning of Power Transmission Dynamics PSCC 2018 [ArXiv] Andrey Y. Lokhov, Deepjyoti Deka, Marc Vuffray, Michael Chertkov Deepjyoti Deka, Armin Zare, Andrey Y. Lokhov, Mihailo Jovanovic, Michael Chertkov 
Andrey Y. Lokhov, Nathan Lemons, Thomas C. McAndrew, Aric Hagberg, Scott Backhaus Short description: Detection of anomalies in cyberphysical systems from real data 
Other Research Projects
Bo Li, David Saad, Andrey Y. Lokhov Short description: Discovery of paradoxical traffic patterns emerging within a new traffic model that includes localized routing inducement, and development of a scalable optimization algorithm for identifying mechanisms to minimize congestion 
Andrey Y. Lokhov, Olga V. Valba, Mikhail V. Tamm, Sergei K. Nechaev Phase transition in random planar diagrams and RNAtype matching Phys. Rev. E 88, 052117 (2013) [pdf] [ArXiv] Andrey Y. Lokhov, Olga V. Valba, Sergei K. Nechaev, Mikhail V. Tamm 