AI agents are increasingly deployed in real-world applications, including systems such as Manus, OpenClaw, and coding agents. Existing research has primarily focused on emph{server-side} efficiency, ...

PyBADS is a Python implementation of the Bayesian Adaptive Direct Search (BADS) algorithm for solving difficult and mildly expensive optimization problems, originally implemented in MATLAB. BADS has ...

This repository contains code to reproduce the experiments reported in "Anubis: Bayesian optimization with unknown feasibility constraints for scientific experimentation".

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...

Sediment plumes created by dredging or mining activities have an impact on the ecosystem in a much larger area than the mining or dredging area itself. It is therefore important and sometimes ...

Abstract: Reinforcement learning (RL) has revolutionized decision-making across a wide range of domains over the past few decades. Yet, deploying RL policies in real-world scenarios presents the ...

School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, U.K. School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, U.K. The Alan Turing Institute, London NW1 2DB, U.K. School ...

BASF Nederland B.V., Arnhem, Netherlands. Understanding and predicting stock price developments and their causes has always been desirable in the financial world. Nowadays, most financial institutions ...

Abstract: Most of the machine learning models have associated hyper-parameters along with their parameters. While the algorithm gives the solution for parameters, its utility for model performance is ...

Despite over 300 y of effort, no solutions exist for predicting when a general planetary configuration will become unstable. We introduce a deep learning architecture to push forward this problem for ...