Floods are among the most destructive natural hazards, particularly in regions with complex terrain and hydrology, where they cause substantial environmental, social, and economic losses. Reliable ...

This Collection supports and amplifies research related to SDG 9 - Industry, Innovation & Infrastructure. Discovering new materials with customizable and optimized properties, driven either by ...

Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...

Abstract: Correctly setting the parameters of a production machine is essential to improve product quality, increase efficiency, and reduce production costs while also supporting sustainability goals.

Abstract: Bayesian optimization (BO) is a powerful surrogate-assisted algorithm for solving expensive black-box optimization problems. While BO was developed for centralized optimization, the ...

https://proceedings.neurips.cc/paper_files/paper/2012/hash/05311655a15b75fab86956663e1819cd-Abstract.html ...

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

In the shown examples from the field of shape optimization and parameter reconstruction, Bayesian optimization, mainly known from machine learning applications, obtains significantly better results in ...

Machine learning has shown tremendous potential for improving the capabilities of network traffic analysis applications, often outperforming simpler rule-based heuristics. However, ML-based solutions ...

The project automatically fetches the latest papers from arXiv based on keywords. The subheadings in the README file represent the search keywords. Only the most recent articles for each keyword are ...