Arbor separates strategy from execution using isolated git worktrees, so engineering teams can finally trace which ...

Each year when MD+DI editors sit down to discuss Medtech Company of the Year prospects, the companies that rise to the top for us tend to be those that have had a transformational year either through ...

Abstract: Bayesian optimization (BO) has emerged as a powerful sample efficient technique for optimizing expensive and time-consuming design of analog circuits. The BO framework leverages ...

This Unity asset provides an end-to-end, Human-in-the-Loop (HITL) Bayesian Optimization workflow (single- and multi-objective) built on botorch.org. It lets you declare design parameters and ...

How likely you think something is to happen depends on what you already believe about the circumstances. That is the simple concept behind Bayes' rule, an approach to calculating probabilities, first ...

Abstract: We propose a novel, scalable deep Bayesian optimization (BO) methodology for designing antennas with a large number of design degrees of freedom. Conventional BO approaches in antenna design ...

Optimizing operational conditions for complex biological systems used in life sciences research and biotechnology is an arduous task. Here, we apply a Bayesian Optimization-based iterative framework ...

Materials design often becomes an expensive black-box optimization problem due to limitations in balancing exploration-exploitation trade-offs in high-dimensional spaces. We propose a reinforcement ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Developing novel materials drives significant breakthroughs ...

In the world of deep learning, finding the right hyperparameters can feel like searching for a needle in a high-dimensional haystack. Even when picking parameters, it is not always easy to know which ...