Search Results for author:
Found 4 papers, 1 papers with code
AI Driven Near Real-time Locational Marginal Pricing Method: A Feasibility and Robustness Study
This study evaluates the performance of popular machine learning and deep learning models in predicting LMP on multiple electricity grids.
Evolving Generalizable Multigrid-Based Helmholtz Preconditioners with Grammar-Guided Genetic Programming
Solving the indefinite Helmholtz equation is not only crucial for the understanding of many physical phenomena but also represents an outstandingly-difficult benchmark problem for the successful application of numerical methods.
Known Operator Learning and Hybrid Machine Learning in Medical Imaging --- A Review of the Past, the Present, and the Future
In this article, we perform a review of the state-of-the-art of hybrid machine learning in medical imaging.
Optimizing Geometric Multigrid Methods with Evolutionary Computation
For many linear and nonlinear systems that arise from the discretization of partial differential equations the construction of an efficient multigrid solver is a challenging task.
