A classifier-guided sampling (CGS) method is introduced for solving engineering design optimization problems with discrete and/or continuous variables and continuous and/or discontinuous responses. The method merges concepts from metamodel-guided sampling and population-based optimization algorithms. The CGS...
[2] [Denoising Diffusion Implicit Models (DDIM) Sampling](https://nn.labml.ai/diffusion/stable_diffusion/sampler/ddim.html) [3] Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole. Score-based generative modeling through stochastic differential equ...
1 INTRODUCTION In this paper, a classifier-guided sampling method is introduced for solving design optimization problems with discrete and/or continuous variables and potentially discontinuous responses. The method merges concepts from metamodel-guided sampling and population-based optimization algorithms to ...
In this paper, a classifier-guided sampling method is presented that can be used for optimization and design space exploration of expensive computer models that have discrete variables and discontinuous responses. The method is tested on a set of example problems. Results show that the method ...
Autonomous Microgrid Design Using Classifier-Guided Sampling.not provided.Peter B. BacklundJohn P. Eddy