Intern
    Data Science Chair

    Physics Informed Deep Learning

    Open Topics

    17.10.2023 | Physics & Deep Learning

    Can AI solve equations?

    Solving equations is hard. So hard that scientists have been developing new methods to do so for the past 2000 years and are still doing so. Why not use neural networks to do it? Mehr
    17.10.2023 | Physics & Deep Learning

    AI-driven scientific discovery

    Can Neural Networks become scientists? Imagine a future where machines, equipped with the ability to autonomously extract governing equations from empirical data, can catalyze breakthroughs in fields like climate science, quantum… Mehr
    07.06.2023 | Physics & Deep Learning

    Data-efficient learning model on the intelligent bridge dataset

    As the state-of-the-art machine learning methods in many fields rely on larger datasets, storing datasets and training models on them becomes significantly more expensive. In the case of sensor-based monitoring of infrastructures,… Mehr
    07.06.2023 | Physics & Deep Learning, Biological&Medical Data

    Improved Identification of Brain Activity to Predict Human Intelligence by using Machine Learning

    Human intelligence is the best predictor of important life outcomes like educational and occupational success and even health and longevity. Mehr
    07.06.2023 | Physics & Deep Learning, Misc.

    Deep Music Composition

    Recent transformer-based generative language models have achieved near human-like performance in generating natural text. In this work, the applicability of these models to deep music generation is investigated. Mehr
    05.06.2023 | Physics & Deep Learning, Ecosystems

    Wettermodelierung mittels Graph Neural Networks

    In vielen Bereichen haben datengetriebene Modelierungsansätze, wie zum Beispiel Deep Learning, bewiesen, dass sie äußerst effizient und präzise sind. Im Bereich der Wettervorhersage zeigen sich hingegen die numerischen Ansätze… Mehr
    05.06.2023 | Physics & Deep Learning

    Unbiased characterization of tremor disorders using Deep Learning for time series analysis

    Massive time series feature extraction is a powerful tool to examine oscillating biological signals (Fulcher and Jones, 2017) such as tremor disorders. Tremor is defined as the involuntary, rhythmical, sinusoidal movement of a… Mehr