Poster
Conditioning by adaptive sampling for robust design
David Brookes · Jennifer Listgarten

Wed Jun 12th 06:30 -- 09:00 PM @ Pacific Ballroom #None

We present a method for design problems wherein the goal is to maximize or specify the value of one or more properties of interest (e.g. maximizing the fluorescence of a protein). We assume access to black box, stochastic oracle" predictive functions, each of which maps from design space to a distribution over properties of interest. Because many state-of-the-art predictive models are known to suffer from pathologies, especially for data far from the training distribution, the problem becomes different from directly optimizing the oracles. Herein, we propose a method to solve this problem that uses model-based adaptive sampling to estimate a distribution over the design space, conditioned on the desired properties.

#### More from the Same Authors

• 2019 Workshop: ICML 2019 Workshop on Computational Biology »
Donna Pe'er · Sandhya Prabhakaran · Elham Azizi · Abdoulaye Baniré Diallo · Anshul Kundaje · Barbara Engelhardt · Wajdi Dhifli · Engelbert MEPHU NGUIFO · Wesley Tansey · Julia Vogt · Jennifer Listgarten · Cassandra Burdziak · Workshop CompBio