Machine learning sequence-function models for proteins could enable significant advances in protein engineering. especially when paired with state-of-the-art methods to select new sequences for property optimization and/or model improvement. Such methods (Bayesian optimization and active learning) require calibrated estimations of model uncertainty. While studies have benchmarked a va... https://unionlosangelers.shop/product-category/headwear/