Review for NeurIPS paper: Multi-Fidelity Bayesian Optimization via Deep Neural Networks

Additional Feedback: POST-REBUTTAL: Thank you for addressing some of my concerns. I am still very keen on seeing larger scale experiments, but appreciate the novelty and technical methodology, which will be useful to the community. Overall, my sentiment of the paper has not changed and I am keeping my score at 6 -- I am still in favour of seeing it accepted, although I am not overly enthusiastic due to the concerns mentioned. In any case, I strongly encourage the authors to continue working on what seems to be a very promising research direction, and to take into account all feedback in order to improve their work. Questions: - in the experiments, why did you use different kernels for the different competing methods?