We are the Machine Learning Group led by Prof. Barbara Hammer at Bielefeld University.
On this page you can find the accompanying source code of our publications 😃
We are the Machine Learning Group led by Prof. Barbara Hammer at Bielefeld University.
On this page you can find the accompanying source code of our publications 😃
A collection of benchmark resources regarding Water Distribution Networks
Go with the Flow: Leveraging Physics-Informed Gradents to Solve Real-World Problems in Water Distribution Systems.
This repository contains the benchmark and the implementation of the experiments from the paper "A Benchmark for Physics-informed Machine Learning of Chlorine States in Water Distribution Networks" by Luca Hermes, André Artelt, Stelios Vrachimis, Marios Polycarpou, and Barbara Hammer
Control of Rayleigh-Bénard Convection: Effectiveness of Reinforcement Learning in the Turbulent Regime
A high-level interface designed for the easy generation of hydraulic and water quality scenario data.
A Python package for implementing and evaluating control algorithms & strategies in smart water networks.
Koopman-Based Surrogate Modeling of Turbulent Rayleigh-Bénard Convection
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