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06/16/2023
AI Driven Near Real-time Locational Marginal Pricing Method: A Feasibility and Robustness Study
Accurate price predictions are essential for market participants in orde...
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05/31/2023
Sensitivity Analysis of High-Dimensional Models with Correlated Inputs
Sensitivity analysis is an important tool used in many domains of comput...
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03/27/2023
Integrated Nested Laplace Approximations for Large-Scale Spatial-Temporal Bayesian Modeling
Bayesian inference tasks continue to pose a computational challenge. Thi...
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05/03/2022
Level-based Blocking for Sparse Matrices: Sparse Matrix-Power-Vector Multiplication
The multiplication of a sparse matrix with a dense vector (SpMV) is a ke...
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04/10/2022
Parallelized integrated nested Laplace approximations for fast Bayesian inference
There is a growing demand for performing larger-scale Bayesian inference...
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08/30/2020
K-way p-spectral clustering on Grassmann manifolds
Spectral methods have gained a lot of recent attention due to the simpli...
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01/29/2020
Reduced-Space Interior Point Methods in Power Grid Problems
Due to critical environmental issues, the power systems have to accommod...
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08/27/2019
High Performance Block Incomplete LU Factorization
Many application problems that lead to solving linear systems make use o...
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07/15/2019
A Recursive Algebraic Coloring Technique for Hardware-Efficient Symmetric Sparse Matrix-Vector Multiplication
The symmetric sparse matrix-vector multiplication (SymmSpMV) is an impor...
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07/11/2019
State-of-The-Art Sparse Direct Solvers
In this chapter we will give an insight into modern sparse elimination m...
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07/11/2019
Structure Exploiting Interior Point Methods
Interior point methods are among the most popular techniques for large s...
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04/25/2018
Optimizing gas networks using adjoint gradients
An increasing amount of gas-fired power plants are currently being insta...
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05/04/2017
