2 citations · 9 across the 8 of their papers we have counts for
3 papers · 1 filter
Multi-Fidelity Bayesian Optimization with Unreliable Information Sources
Petrus Mikkola, Julien Martinelli, Louis Filstroff +1
Bayesian optimization (BO) is a powerful framework for optimizing black-box, expensive-to-evaluate functions. Over the past decade, many algorithms have been proposed to integrate…
Bayesian Optimization Augmented with Actively Elicited Expert Knowledge
Daolang Huang, Louis Filstroff, Petrus Mikkola +2
Bayesian optimization (BO) is a well-established method to optimize black-box functions whose direct evaluations are costly. In this paper, we tackle the problem of incorporating e…
Approximate Bayesian Computation with Domain Expert in the Loop
Ayush Bharti, Louis Filstroff, Samuel Kaski
Approximate Bayesian computation (ABC) is a popular likelihood-free inference method for models with intractable likelihood functions. As ABC methods usually rely on comparing summ…