Hello,
i am trying to implement a multi-fidelity bayesian optimization to solve an inverse problem. I have two sources for my data: an analytical solution, which is fast and cheap and a simulation, which is very slow. I read the tutorial about mfKG but in this example the fidelity level is random from 0 to 1. Can I use this example for my case and bound the fidelity-levels to be either 0 or 1? Or what would be a suggestion for an acquisition function to predict the next fidelity-level?
Thank you !
Hello, i am trying to implement a multi-fidelity bayesian optimization to solve an inverse problem. I have two sources for my data: an analytical solution, which is fast and cheap and a simulation, which is very slow. I read the tutorial about mfKG but in this example the fidelity level is random from 0 to 1. Can I use this example for my case and bound the fidelity-levels to be either 0 or 1? Or what would be a suggestion for an acquisition function to predict the next fidelity-level? Thank you !