@Cambridge_Uni Grad - Astrophysics | @join_EF alumni | a tired MedTech founder and entrepreneur | hoping to take a break and do PhD in applying 
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Besides examples in the paper, one-shot KG performs better than qNEI, which tends to perform better than implementations f EI we've tested. KG is particularly useful for multi-fidelity optimization, for which we see great performance on AutoML and simulation optimization tasks.
Thanks. I’m coming from a physics background, so found myself getting a bit lost in section 4.2 of the paper. But I’m really excited to try out BoTORCH!
Glad to hear! If you aren't doing BayesOpt research, I would recommend giving Ax (http://ax.dev ) a try. This is the front-end interface to BoTorch, and it provides an easy to use interface to one-shot KG and multi-fidelity variants.
That’s incredibly helpful. I graduated from Cambridge in physics last year and now just trying my best to transition into machine learning by devouring every ML paper I get the chance to read. Increasingly I’m finding myself drawn to causal inference. GP seems popular too!
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