Article citations More>> Snoek, J., Larochelle, H. and Adams, R.P. (2012) Practical Bayesian Optimization of Machine Learning Algorithms. arXiv: 1206.2944. has been cited by the following article: ...

We base our algorithm on GoOSE, an algorithm for safe and sample-efficient Bayesian optimization, for handling performance and stability criteria. We introduce multiple computational and algorithmic ...

A novel optimization technique enhances the speed and accuracy of Bayesian inference, streamlining scientific research by automating complex calculations and offering reliable uncertainty estimates.

In response to this issue, this study improved the dragonfly swarm optimization algorithm and solved the problem of variable type conflicts through binary discretization, applying it to the Bayesian ...

Automation and optimization of chemical systems require well-informed decisions on what experiments to run to reduce time, materials, and/or computations. Data-driven active learning algorithms have ...