1 code implementation • 26 Apr 2024 • Richard Michael, Simon Bartels, Miguel González-Duque, Yevgen Zainchkovskyy, Jes Frellsen, Søren Hauberg, Wouter Boomsma
To optimize efficiently over discrete data and with only few available target observations is a challenge in Bayesian optimization.
no code implementations • 10 Nov 2022 • Yevgen Zainchkovskyy, Jesper Ferkinghoff-Borg, Anja Bennett, Thomas Egebjerg, Nikolai Lorenzen, Per Jr. Greisen, Søren Hauberg, Carsten Stahlhut
Pre-trained protein language models have demonstrated significant applicability in different protein engineering task.
no code implementations • NeurIPS 2021 • Pierre Segonne, Yevgen Zainchkovskyy, Søren Hauberg
As one cannot train without data, we provide mechanisms for generating pseudo-inputs in informative low-density regions of the input space, and show how to leverage these in a practical Bayesian framework that casts a prior distribution over the model uncertainty.