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Found 5 papers, 1 papers with code
An Efficient Multi Quantile Regression Network with Ad Hoc Prevention of Quantile Crossing
This article presents the Sorting Composite Quantile Regression Neural Network (SCQRNN), an advanced quantile regression model designed to prevent quantile crossing and enhance computational efficiency.
From Structured to Unstructured:A Comparative Analysis of Computer Vision and Graph Models in solving Mesh-based PDEs
This article investigates the application of computer vision and graph-based models in solving mesh-based partial differential equations within high-performance computing environments.
Enhancing Multi-Objective Optimization through Machine Learning-Supported Multiphysics Simulation
This paper presents a methodological framework for training, self-optimising, and self-organising surrogate models to approximate and speed up multiobjective optimisation of technical systems based on multiphysics simulations.
DADO -- Low-Cost Query Strategies for Deep Active Design Optimization
We present two selection strategies for self-optimization to reduce the computational cost in multi-objective design optimization problems.
Dataset of a parameterized U-bend flow for Deep Learning Applications
This third representation enables considering the specific data structure of numerical simulations for deep learning approaches.
