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09/13/2023
Geospatial Tessellation in the Agent-In-Cell Model: A Framework for Agent-Based Modeling of Pandemic
Agent-based simulation is a versatile and potent computational modeling ...
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08/14/2023
U-Turn Diffusion
We present a comprehensive examination of score-based diffusion models o...
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04/04/2023
Control of Line Pack in Natural Gas System: Balancing Limited Resources under Uncertainty
We build and experiment with a realistic but reduced natural gas model o...
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03/31/2023
A Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study
This paper addresses the challenge of efficiently solving the optimal po...
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03/16/2023
Universality and Control of Fat Tails
Motivated by applications in hydrodynamics and networks of thermostatica...
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01/25/2023
Exact Fractional Inference via Re-Parametrization Interpolation between Tree-Re-Weighted- and Belief Propagation- Algorithms
Inference efforts – required to compute partition function, Z, of an Isi...
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08/27/2022
Statistical Mechanics of Thermostatically Controlled Multi-Zone Buildings
We study the collective phenomena and constraints associated with the ag...
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05/23/2022
Machine Learning for Electricity Market Clearing
This paper seeks to design a machine learning twin of the optimal power ...
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10/26/2021
Model Reduction of Swing Equations with Physics Informed PDE
This manuscript is the first step towards building a robust and efficien...
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10/25/2021
Physics Informed Machine Learning of SPH: Machine Learning Lagrangian Turbulence
Smoothed particle hydrodynamics (SPH) is a mesh-free Lagrangian method f...
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04/07/2021
Which Neural Network to Choose for Post-Fault Localization, Dynamic State Estimation and Optimal Measurement Placement in Power Systems?
We consider a power transmission system monitored with Phasor Measuremen...
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03/26/2021
Embedding Power Flow into Machine Learning for Parameter and State Estimation
Modern state and parameter estimations in power systems consist of two s...
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02/16/2021
Message Passing Descent for Efficient Machine Learning
We propose a new iterative optimization method for the Data-Fitting (DF)...
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02/12/2021
Physics-Informed Graphical Neural Network for Parameter State Estimations in Power Systems
Parameter Estimation (PE) and State Estimation (SE) are the most wide-sp...
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01/28/2021
Neural Particle Image Velocimetry
In the past decades, great progress has been made in the field of optica...
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05/05/2020
A Hierarchical Approach to Multi-Energy Demand Response: From Electricity to Multi-Energy Applications
Due to proliferation of energy efficiency measures and availability of t...
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04/20/2020
Data-Driven Learning and Load Ensemble Control
Demand response (DR) programs aim to engage distributed small-scale flex...
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10/22/2019
Tractable Minor-free Generalization of Planar Zero-field Ising Models
We present a new family of zero-field Ising models over N binary variabl...
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06/14/2019
A New Family of Tractable Ising Models
We present a new family of zero-field Ising models over N binary variabl...
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01/03/2019
Learning a Generator Model from Terminal Bus Data
In this work we investigate approaches to reconstruct generator models f...
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12/22/2018
Inference and Sampling of K_33-free Ising Models
We call an Ising model tractable when it is possible to compute its part...
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11/12/2018
Gauges, Loops, and Polynomials for Partition Functions of Graphical Models
We suggest a new methodology for analysis and approximate computations o...
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10/16/2018
From Deep to Physics-Informed Learning of Turbulence: Diagnostics
We describe physical tests validating progress made toward acceleration ...
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10/11/2018
Real-time Fault Localization in Power Grids With Convolutional Neural Networks
Diverse fault types, fast re-closures and complicated transient states a...
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03/17/2018
Topology Estimation using Graphical Models in Multi-Phase Power Distribution Grids
Distribution grid is the medium and low voltage part of a large power sy...
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03/14/2018
Bucket Renormalization for Approximate Inference
Probabilistic graphical models are a key tool in machine learning applic...
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01/05/2018
Gauged Mini-Bucket Elimination for Approximate Inference
Computing the partition function Z of a discrete graphical model is a fu...
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10/27/2017
Online Learning of Power Transmission Dynamics
We consider the problem of reconstructing the dynamic state matrix of tr...
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10/20/2017
Belief Propagation Min-Sum Algorithm for Generalized Min-Cost Network Flow
Belief Propagation algorithms are instruments used broadly to solve grap...
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10/19/2017
Importance sampling the union of rare events with an application to power systems analysis
This paper presents a method for estimating the probability μ of a union...
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07/07/2017
Methodology for Multi-stage, Operations- and Uncertainty-Aware Placement and Sizing of FACTS Devices in a Large Power Transmission System
We develop new optimization methodology for planning installation of Fle...
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07/05/2017
Topology Estimation in Bulk Power Grids: Guarantees on Exact Recovery
The topology of a power grid affects its dynamic operation and settlemen...
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03/03/2017
Gauging Variational Inference
Computing partition function is the most important statistical inference...
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06/21/2016
Graphical Models for Optimal Power Flow
Optimal power flow (OPF) is the central optimization problem in electric...
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05/29/2016
MCMC assisted by Belief Propagaion
Markov Chain Monte Carlo (MCMC) and Belief Propagation (BP) are the most...
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05/24/2016
Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models
We consider the problem of learning the underlying graph of an unknown I...
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09/23/2015
Minimum Weight Perfect Matching via Blossom Belief Propagation
Max-product Belief Propagation (BP) is a popular message-passing algorit...
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02/03/2015
Learning Planar Ising Models
Inference and learning of graphical models are both well-studied problem...
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08/09/2014
Approximate inference on planar graphs using Loop Calculus and Belief Propagation
We introduce novel results for approximate inference on planar graphical...
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06/05/2013
Loop Calculus and Bootstrap-Belief Propagation for Perfect Matchings on Arbitrary Graphs
This manuscript discusses computation of the Partition Function (PF) and...
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05/17/2013
