vix.ing · top · new · best · stats · spec

Chertkov, Michael

  1. Sparsity-Promoting Optimal Wide-Area Control of Power Networks
    2013/07/16 by Florian Dörfler, Mihailo R. Jovanović, Dörfler, Florian +5 · 5 citations
    Computer Science · Mathematics · Engineering · #Nonlinear Dynamics and Pattern Formation #Numerical methods for differential equations #Power System Optimization and Stability
  2. Chance Constrained Optimal Power Flow: Risk-Aware Network Control under Uncertainty
    2012/09/25 by Daniel Bienstock, Michael Chertkov, Bienstock, Daniel +3 · 4 citations
    Engineering · Environmental Science · #Energy Load and Power Forecasting #Wind and Air Flow Studies #Thermal Analysis in Power Transmission
  3. Optimal structure and parameter learning of Ising models
    2016/12/15 by Andrey Y. Lokhov, Marc Vuffray, Lokhov, Andrey Y. +5 · 5 citations
    Mathematics · Biochemistry, Genetics and Molecular Biology · Materials Science · #Markov Chains and Monte Carlo Methods #Protein Structure and Dynamics #Machine Learning in Materials Science
  4. Embedding Hard Physical Constraints in Neural Network Coarse-Graining of\n 3D Turbulence
    2020/01/31 by Arvind Mohan, Nicholas Lubbers, Mohan, Arvind T. +5 · 5 citations
    Physics and Astronomy · Engineering · Computer Science · #Model Reduction and Neural Networks #Lattice Boltzmann Simulation Studies #Generative Adversarial Networks and Image Synthesis
  5. Predicting Failures in Power Grids: The Case of Static Overloads
    2010/06/03 by Chertkov, Michael, Pan, Feng, Stepanov, Mikhail G. · 1 citation
    #FOS: Mathematics #FOS: Physical sciences #Optimization and Control (math.OC) #Physics and Society (physics.soc-ph)
  6. Learning Planar Ising Models
    2010/11/15 by Johnson, Jason K., Netrapalli, Praneeth, Chertkov, Michael · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (stat.ML)
  7. Exact and Efficient Algorithm to Discover Extreme Stochastic Events in\n Wind Generation over Transmission Power Grids
    2011/04/01 by Michael Chertkov, Михаил Степанов, Chertkov, Michael +5 · 1 citation
    Engineering · #Energy Load and Power Forecasting
  8. Approximate inference on planar graphs using Loop Calculus and Belief Propagation
    2014/08/09 by Gomez, Vicenc, Kappen, Hilbert, Chertkov, Michael · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences
  9. Efficient Synchronization Stability Metrics for Fault Clearing
    2014/09/15 by Backhaus, Scott, Bent, Russell, Bienstock, Daniel +2 · 1 citation
    #FOS: Electrical engineering #FOS: Mathematics #Optimization and Control (math.OC) #Systems and Control (eess.SY) #electronic engineering #information engineering
  10. A differential analysis of the power flow equations
    2015/06/28 by Dvijotham, Krishnamurthy, Chertkov, Michael, Low, Steven · 1 citation
    #FOS: Electrical engineering #Systems and Control (eess.SY) #electronic engineering #information engineering
  11. Learning Topology of Distribution Grids using only Terminal Node Measurements
    2016/08/17 by Deka, Deepjyoti, Backhaus, Scott, Chertkov, Michael · 1 citation
    #FOS: Electrical engineering #FOS: Mathematics #Optimization and Control (math.OC) #Systems and Control (eess.SY) #electronic engineering #information engineering
  12. Importance sampling the union of rare events with an application to power systems analysis
    2017/10/19 by Owen, Art B., Maximov, Yury, Chertkov, Michael · 1 citation
    #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Numerical Analysis (math.NA)
  13. Exact Topology and Parameter Estimation in Distribution Grids with\n Minimal Observability
    2017/10/29 by Sejun Park, Deepjyoti Deka, Park, Sejun +3 · 1 citation
    Engineering · #Electric Power System Optimization #FOS: Electrical engineering #Optimal Power Flow Distribution #Power System Optimization and Stability #Systems and Control (eess.SY) #electronic engineering #information engineering
  14. Optimal Load Ensemble Control in Chance-Constrained Optimal Power Flow
    2018/05/23 by Hassan, Ali, Mieth, Robert, Chertkov, Michael +2 · 1 citation
    #FOS: Electrical engineering #Systems and Control (eess.SY) #electronic engineering #information engineering
  15. Topology Estimation using Graphical Models in Multi-Phase Power\n Distribution Grids
    2018/03/17 by Deepjyoti Deka, Deka, Deepjyoti, Michael Chertkov +3 · 1 citation
    Computer Science · #Blind Source Separation Techniques #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Image and Signal Denoising Methods #Machine Learning (stat.ML) #Neural Networks and Applications #Optimization and Control (math.OC) #Systems and Control (eess.SY) #electronic engineering #information engineering
  16. Real-time Faulted Line Localization and PMU Placement in Power Systems through Convolutional Neural Networks
    2018/10/11 by Li, Wenting, Deka, Deepjyoti, Chertkov, Michael +1 · 1 citation
    #FOS: Computer and information sciences #FOS: Electrical engineering #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Systems and Control (eess.SY) #electronic engineering #information engineering
  17. Controlled Tripping of Overheated Lines Mitigates Power Outages
    2011/04/23 by René Pfitzner, Pfitzner, René, Konstantin Turitsyn +3 · 1 citation
    Engineering · #FOS: Electrical engineering #FOS: Mathematics #FOS: Physical sciences #Optimal Power Flow Distribution #Optimization and Control (math.OC) #Physics and Society (physics.soc-ph) #Power System Optimization and Stability #Power System Reliability and Maintenance #Systems and Control (eess.SY) #electronic engineering #information engineering
  18. Compressed Convolutional LSTM: An Efficient Deep Learning framework to\n Model High Fidelity 3D Turbulence
    2019/02/28 by Arvind Mohan, Mohan, Arvind, Don Daniel +6 · 3 citations
    Computer Science · Physics and Astronomy · Engineering · #Generative Adversarial Networks and Image Synthesis #Model Reduction and Neural Networks #Fluid Dynamics and Turbulent Flows
  19. Belief Propagation and Beyond for Particle Tracking
    2008/06/06 by Michael Chertkov, Chertkov, Michael, Lukáš Kroc +3 · 1 citation
    Computer Science · Mathematics · #Gaussian Processes and Bayesian Inference #Markov Chains and Monte Carlo Methods #Target Tracking and Data Fusion in Sensor Networks
  20. A Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study
    2023/03/31 by Robert Ferrando, Laurent Pagnier, Ferrando, Robert +11 · 1 citation
    Engineering · #Electric Power System Optimization #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Machine Learning (cs.LG) #Optimal Power Flow Distribution #Optimization and Control (math.OC) #Power System Optimization and Stability #Systems and Control (eess.SY) #electronic engineering #information engineering
  21. Space-Time Diffusion Bridge
    2024/02/13 by Hamidreza Behjoo, Behjoo, Hamidreza, Michael Chertkov +1 · 3 citations
    Engineering · #FOS: Computer and information sciences #Geophysics and Sensor Technology #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Structural Response to Dynamic Loads #Transportation Safety and Impact Analysis
  22. Sampling Decisions: Exact Path-Space Correction, Prior Cancellation and Local-Boltzmann Guidance
    2025/03/17 by Michael Chertkov, Chertkov, Michael, Sungsoo Ahn +3 · 3 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Gaussian Processes and Bayesian Inference #Reinforcement Learning in Robotics #cond-mat.stat-mech #cs.AI #cs.LG #cs.SY #eess.SY #stat.ML
  23. Turbulence forecasting via Neural ODE
    2019/11/12 by Gavin Portwood, Peetak Mitra, Portwood, Gavin D. +21 · 1 citation
    Earth and Planetary Sciences · Engineering · Physics and Astronomy · #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Fluid Dynamics and Turbulent Flows #Meteorological Phenomena and Simulations #Model Reduction and Neural Networks
  24. Mixing Artificial and Natural Intelligence: From Statistical Mechanics to AI and Back to Turbulence
    2024/03/26 by Chertkov, Michael · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Machine Learning (cs.LG) #Statistical Mechanics (cond-mat.stat-mech)
  25. Physics-Guided Actor-Critic Reinforcement Learning for Swimming in Turbulence
    2024/06/05 by Christopher Koh, Laurent Pagnier, Koh, Christopher +3 · 2 citations
    Computer Science · Economics, Econometrics and Finance · #Chaotic Dynamics (nlin.CD) #Complex Systems and Time Series Analysis #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Reservoir Computing #Reinforcement Learning in Robotics #Systems and Control (eess.SY) #electronic engineering #information engineering