Michael Chertkov

ORCID

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 122

Top Venues

CoRR

CDC

IEEE Trans. Control. Netw. Syst.

ACC

Publications

Hamidreza Behjoo, Michael Chertkov
Space-Time Bridge-Diffusion. CoRR (2024)
Michael Chertkov
Mixing Artificial and Natural Intelligence: From Statistical Mechanics to AI and Back to Turbulence. CoRR (2024)
Christopher Koh, Laurent Pagnier, Michael Chertkov
Physics-Informed Critic in an Actor-Critic Reinforcement Learning for Swimming in Turbulence. CoRR (2024)
Criston Hyett, Laurent Pagnier, Jean Alisse, Lilach Sabban, Igal Goldshtein, Michael Chertkov
Control of Line Pack in Natural Gas System: Balancing Limited Resources under Uncertainty. CoRR (2023)
Michael Chertkov
Universality and Control of Fat Tails. CoRR (2023)
Michael Chertkov
Universality and Control of Fat Tails. IEEE Control. Syst. Lett. 7 (2023)
Robert Ferrando, Laurent Pagnier, Robert Mieth, Zhirui Liang, Yury Dvorkin, Daniel Bienstock, Michael Chertkov
A Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study. CoRR (2023)
Hamidreza Behjoo, Michael Chertkov
U-Turn Diffusion. CoRR (2023)
Laurent Pagnier, Igal Goldshtein, Criston Hyett, Robert Ferrando, Jean Alisse, Lilah Saban, Michael Chertkov
System-Wide Emergency Policy for Transitioning from Main to Secondary Fuel. CoRR (2023)
Hamidreza Behjoo, Michael Chertkov
Exact Fractional Inference via Re-Parametrization & Interpolation between Tree-Re-Weighted- and Belief Propagation- Algorithms. CoRR (2023)
Amir Mohammad Esmaieeli Sikaroudi, Alon Efrat, Michael Chertkov
Geospatial Tessellation in the Agent-In-Cell Model: A Framework for Agent-Based Modeling of Pandemic. CoRR (2023)
Laurent Pagnier, Julian Fritzsch, Philippe Jacquod, Michael Chertkov
Toward Model Reduction for Power System Transients With Physics-Informed PDE. IEEE Access 10 (2022)
Laurent Pagnier, Robert Ferrando, Yury Dvorkin, Michael Chertkov
Machine Learning for Electricity Market Clearing. CoRR (2022)
Lucas Fuentes Valenzuela, Lindell Williams, Michael Chertkov
Statistical Mechanics of Thermostatically Controlled Multi-Zone Buildings. CoRR (2022)
Michael Woodward, Yifeng Tian, Criston Hyett, Chris Fryer, Daniel Livescu, Mikhail Stepanov, Michael Chertkov
Physics Informed Machine Learning of SPH: Machine Learning Lagrangian Turbulence. CoRR (2021)
Andrei Afonin, Michael Chertkov
Which Neural Network to Choose for Post-Fault Localization, Dynamic State Estimation, and Optimal Measurement Placement in Power Systems? Frontiers Big Data 4 (2021)
Laurent Pagnier, Michael Chertkov
Embedding Power Flow into Machine Learning for Parameter and State Estimation. CoRR (2021)
Mikhail Krechetov, Amir Mohammad Esmaieeli Sikaroudi, Alon Efrat, Valentin Polishchuk, Michael Chertkov
Prediction and Prevention of Pandemics via Graphical Model Inference and Convex Programming. CoRR (2021)
Laurent Pagnier, Michael Chertkov
Physics-Informed Graphical Neural Network for Parameter & State Estimations in Power Systems. CoRR (2021)
Francesco Concetti, Michael Chertkov
Message Passing Descent for Efficient Machine Learning. CoRR (2021)
Andrei Afonin, Michael Chertkov
Which Neural Network to Choose for Post-Fault Localization, Dynamic State Estimation and Optimal Measurement Placement in Power Systems? CoRR (2021)
Laurent Pagnier, Michael Chertkov, Julian Fritzsch, Philippe Jacquod
Model Reduction of Swing Equations with Physics Informed PDE. CoRR (2021)
Nikolay Stulov, Michael Chertkov
Neural Particle Image Velocimetry. CoRR (2021)
Deepjyoti Deka, Michael Chertkov, Scott Backhaus
Joint Estimation of Topology and Injection Statistics in Distribution Grids With Missing Nodes. IEEE Trans. Control. Netw. Syst. 7 (3) (2020)
Ali Hassan, Samrat Acharya, Michael Chertkov, Deepjyoti Deka, Yury Dvorkin
A Hierarchical Approach to Multienergy Demand Response: From Electricity to Multienergy Applications. Proc. IEEE 108 (9) (2020)
Michael Chertkov, Göran Andersson
Multienergy Systems. Proc. IEEE 108 (9) (2020)
Saurav Talukdar, Deepjyoti Deka, Harish Doddi, Donatello Materassi, Michael Chertkov, Murti V. Salapaka
Physics informed topology learning in networks of linear dynamical systems. Autom. 112 (2020)
Sejun Park, Deepjyoti Deka, Scott Backhaus, Michael Chertkov
Learning With End-Users in Distribution Grids: Topology and Parameter Estimation. IEEE Trans. Control. Netw. Syst. 7 (3) (2020)
Nikolay N. Novitsky, Zoya I. Shalaginova, Aleksandr A. Alekseev, Vyacheslav V. Tokarev, Oksana A. Grebneva, Aleksandr V. Lutsenko, Olga V. Vanteeva, Egor A. Mikhailovsky, Roman Pop, Petr Vorobev, Michael Chertkov
Smarter Smart District Heating. Proc. IEEE 108 (9) (2020)
Deepjyoti Deka, Saurav Talukdar, Michael Chertkov, Murti V. Salapaka
Graphical Models in Meshed Distribution Grids: Topology Estimation, Change Detection & Limitations. IEEE Trans. Smart Grid 11 (5) (2020)
Ali Hassan, Deepjyoti Deka, Michael Chertkov, Yury Dvorkin
Data-Driven Learning and Load Ensemble Control. CoRR (2020)
Ilia Luchnikov, David Métivier, Henni Ouerdane, Michael Chertkov
Super-relaxation of space-time-quantized ensemble of energy loads. CoRR (2020)
Ali Hassan, Samrat Acharya, Michael Chertkov, Deepjyoti Deka, Yury Dvorkin
A Hierarchical Approach to Multi-Energy Demand Response: From Electricity to Multi-Energy Applications. CoRR (2020)
Valerii Likhosherstov, Yury Maximov, Michael Chertkov
A New Family of Tractable Ising Models. CoRR (2019)
Yize Chen, Md Umar Hashmi, Deepjyoti Deka, Michael Chertkov
Stochastic Battery Operations using Deep Neural Networks. ISGT (2019)
Michael Chertkov, Mihailo R. Jovanovic, Bernard C. Lesieutre, Steven H. Low, Pascal Van Hentenryck, Louis Wehenkel
Guest Editorial Special Issue on Analysis, Control, and Optimization of Energy Networks. IEEE Trans. Control. Netw. Syst. 6 (3) (2019)
Vladimir Frolov, Priyanko Guha Thakurta, Scott Backhaus, Janusz W. Bialek, Michael Chertkov
Operations- and Uncertainty-Aware Installation of FACTS Devices in a Large Transmission System. IEEE Trans. Control. Netw. Syst. 6 (3) (2019)
Nikolay Stulov, Dejan J. Sobajic, Yury Maximov, Deepjyoti Deka, Michael Chertkov
Learning a Generator Model from Terminal Bus Data. CoRR (2019)
Ali Hassan, Robert Mieth, Michael Chertkov, Deepjyoti Deka, Yury Dvorkin
Optimal Load Ensemble Control in Chance-Constrained Optimal Power Flow. IEEE Trans. Smart Grid 10 (5) (2019)
Deepjyoti Deka, Saurav Talukdar, Michael Chertkov, Murti V. Salapaka
Graphical Models in Loopy Distribution Grids: Topology estimation, change detection and limitation. CoRR (2019)
Roman Pop, Ali Hassan, Kenneth Bruninx, Michael Chertkov, Yury Dvorkin
A Markov Process Approach to Ensemble Control of Smart Buildings. CoRR (2019)
Valerii Likhosherstov, Yury Maximov, Michael Chertkov
Tractable Minor-free Generalization of Planar Zero-field Ising Models. CoRR (2019)
Michael Chertkov, Yury Maximov
Gauges, Loops, and Polynomials for Partition Functions of Graphical Models. CoRR (2018)
Deepjyoti Deka, Scott Backhaus, Michael Chertkov
Structure Learning in Power Distribution Networks. IEEE Trans. Control. Netw. Syst. 5 (3) (2018)
Colin Grudzien, Deepjyoti Deka, Michael Chertkov, Scott N. Backhaus
Structure- and Physics-Preserving Reductions of Power Grid Models. Multiscale Model. Simul. 16 (4) (2018)
David Métivier, Ilia Luchnikov, Michael Chertkov
Power of Ensemble Diversity and Randomization for Energy Aggregation. CoRR (2018)
Saurav Talukdar, Deepjyoti Deka, Michael Chertkov, Murti V. Salapaka
Topology Learning of Radial Dynamical Systems with Latent Nodes. ACC (2018)
Sungsoo Ahn, Michael Chertkov, Jinwoo Shin, Adrian Weller
Gauged Mini-Bucket Elimination for Approximate Inference. AISTATS (2018)
Andrii Riazanov, Yury Maximov, Michael Chertkov
Belief Propagation Min-Sum Algorithm for Generalized Min-Cost Network Flow. ACC (2018)
Saurav Talukdar, Deepjyoti Deka, Michael Chertkov, Murti V. Salapaka
Topology Learning of Radial Dynamical Systems with Latent Nodes. CoRR (2018)
Ryan King, Oliver Hennigh, Arvind Mohan, Michael Chertkov
From Deep to Physics-Informed Learning of Turbulence: Diagnostics. CoRR (2018)
Sungsoo Ahn, Michael Chertkov, Andrew E. Gelfand, Sejun Park, Jinwoo Shin
Maximum Weight Matching Using Odd-Sized Cycles: Max-Product Belief Propagation and Half-Integrality. IEEE Trans. Inf. Theory 64 (3) (2018)
Valerii Likhosherstov, Yury Maximov, Michael Chertkov
-free Ising Models. CoRR (2018)
Sejun Park, Deepjyoti Deka, Michael Chertkov
Learning in Power Distribution Grids under Correlated Injections. ACSSC (2018)
David Métivier, Michael Chertkov
Mean Field Control for Efficient Mixing of Energy Loads. CoRR (2018)
Andrey Y. Lokhov, Deepjyoti Deka, Marc Vuffray, Michael Chertkov
Uncovering Power Transmission Dynamic Model from Incomplete PMU Observations. CDC (2018)
Sungsoo Ahn, Michael Chertkov, Adrian Weller, Jinwoo Shin
Bucket Renormalization for Approximate Inference. ICML (2018)
Deepjyoti Deka, Michael Chertkov, Scott Backhaus
Joint Estimation of Topology \& Injection Statistics in Distribution Grids with Missing Nodes. CoRR (2018)
Ali Hassan, Robert Mieth, Michael Chertkov, Deepjyoti Deka, Yury Dvorkin
Optimal Load Ensemble Control in Chance-Constrained Optimal Power Flow. CoRR (2018)
Wenting Li, Deepjyoti Deka, Michael Chertkov, Meng Wang
Real-time Fault Localization in Power Grids With Convolutional Neural Networks. CoRR (2018)
Deepjyoti Deka, Michael Chertkov, Scott Backhaus
Topology Estimation using Graphical Models in Multi-Phase Power Distribution Grids. CoRR (2018)
Sejun Park, Deepjyoti Deka, Scott Backhaus, Michael Chertkov
Learning with End-Users in Distribution Grids: Topology and Parameter Estimation. 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)
Michael Chertkov, Alexander Korotkevich
Adiabatic approach for natural gas pipeline computations. CoRR (2017)
Ali Hassan, Yury Dvorkin, Deepjyoti Deka, Michael Chertkov
Chance-Constrained ADMM Approach for Decentralized Control of Distributed Energy Resources. CoRR (2017)
Krishnamurthy Dvijotham, Michael Chertkov, Pascal Van Hentenryck, Marc Vuffray, Sidhant Misra
Graphical models for optimal power flow. Constraints An Int. J. 22 (1) (2017)
Michael Chertkov, Vladimir Y. Chernyak
Ensemble of Thermostatically Controlled Loads: Statistical Physics Approach. CoRR (2017)
Deepjyoti Deka, Saurav Talukdar, Michael Chertkov, Murti V. Salapaka
Topology Estimation in Bulk Power Grids: Guarantees on Exact Recovery. CoRR (2017)
Sungsoo Ahn, Michael Chertkov, Jinwoo Shin
Gauging Variational Inference. NIPS (2017)
Michael Chertkov, Deepjyoti Deka, Yury Dvorkin
Optimal Ensemble Control of Loads in Distribution Grids with Network Constraints. CoRR (2017)
Art B. Owen, Yury Maximov, Michael Chertkov
Importance sampling the union of rare events with an application to power systems analysis. CoRR (2017)
Michael Chertkov, Sidhant Misra, Marc Vuffray, Dvijotham Krishnamurty, Pascal Van Hentenryck
Graphical Models and Belief Propagation-hierarchy for Optimal Physics-Constrained Network Flows. CoRR (2017)
Michael Chertkov, Vladimir Y. Chernyak
Ensemble Control of Cycling Energy Loads: Markov Decision Approach. CoRR (2017)
Michael Chertkov, Alexander Korotkevich
Adiabatic approach for natural gas pipeline computations. CDC (2017)
Saurav Talukdar, Deepjyoti Deka, Blake Lundstrom, Michael Chertkov, Murti V. Salapaka
Learning Exact Topology of a Loopy Power Grid from Ambient Dynamics. e-Energy (2017)
Sejun Park, Deepjyoti Deka, Michael Chertkov
Exact Topology and Parameter Estimation in Distribution Grids with Minimal Observability. CoRR (2017)
Andrey Y. Lokhov, Marc Vuffray, Dmitry Shemetov, Deepjyoti Deka, Michael Chertkov
Online Learning of Power Transmission Dynamics. CoRR (2017)
Vladimir A. Frolov, Michael Chertkov
Methodology for Multi-stage, Operations- and Uncertainty-Aware Placement and Sizing of FACTS Devices in a Large Power Transmission System. CoRR (2017)
Michael Chertkov, Nikolai N. Novitsky
Thermal Transients in District Heating Systems. CoRR (2017)
Michael Chertkov, Yury Dvorkin
Chance constrained optimal power flow with primary frequency response. CDC (2017)
Andrii Riazanov, Yury Maximov, Michael Chertkov
Belief Propagation Min-Sum Algorithm for Generalized Min-Cost Network Flow. CoRR (2017)
Sidhant Misra, Marc Vuffray, Andrey Y. Lokhov, Michael Chertkov
Towards Optimal Sparse Inverse Covariance Selection through Non-Convex Optimization. CoRR (2017)
Colin Grudzien, Deepjyoti Deka, Michael Chertkov, Scott Backhaus
Structure- & Physics- Preserving Reductions of Power Grid Models. CoRR (2017)
Deepjyoti Deka, Michael Chertkov, Scott Backhaus
Estimating topology and injection statistics in distribution grids with hidden nodes. SmartGridComm (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)
Sungsoo Ahn, Michael Chertkov, Jinwoo Shin
Synthesis of MCMC and Belief Propagation. NIPS (2016)
Sungsoo Ahn, Michael Chertkov, Jinwoo Shin
MCMC assisted by Belief Propagaion. CoRR (2016)
Anatoly Zlotnik, Line Roald, Scott Backhaus, Michael Chertkov, Göran Andersson
Control policies for operational coordination of electric power and natural gas transmission systems. ACC (2016)
Deepjyoti Deka, Scott Backhaus, Michael Chertkov
Estimating Distribution Grid Topologies: A Graphical Learning based Approach. CoRR (2016)
Marc Vuffray, Sidhant Misra, Andrey Y. Lokhov, Michael Chertkov
Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models. NIPS (2016)
Jason K. Johnson, Diane Oyen, Michael Chertkov, Praneeth Netrapalli
Learning Planar Ising Models. J. Mach. Learn. Res. 17 (2016)
Deepjyoti Deka, Scott Backhaus, Michael Chertkov
Tractable structure learning in radial physical flow networks. CDC (2016)
Krishnamurthy Dvijotham, Pascal Van Hentenryck, Michael Chertkov, Sidhant Misra, Marc Vuffray
Graphical Models for Optimal Power Flow. CoRR (2016)
Line Roald, Göran Andersson, Sidhant Misra, Michael Chertkov, Scott Backhaus
Optimal power flow with wind power control and limited expected risk of overloads. PSCC (2016)
Deepjyoti Deka, Scott Backhaus, Michael Chertkov
Learning topology of the power distribution grid with and without missing data. ECC (2016)
Deepjyoti Deka, Scott Backhaus, Michael Chertkov
Tractable Structure Learning in Radial Physical Flow Networks. CoRR (2016)
Line Roald, Sidhant Misra, Michael Chertkov, Scott Backhaus, Göran Andersson
Chance Constrained Optimal Power Flow with Curtailment and Reserves from Wind Power Plants. CoRR (2016)
Deepjyoti Deka, Scott Backhaus, Michael Chertkov
Learning Topology of Distribution Grids using only Terminal Node Measurements. CoRR (2016)
Krishnamurthy Dvijotham, Michael Chertkov, Steven H. Low
Monotone operator approach to power flow solutions. ACC (2016)
Marc Vuffray, Sidhant Misra, Andrey Y. Lokhov, Michael Chertkov
Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models. CoRR (2016)

Michael Chertkov.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Michael Chertkov