Deutsch Intern
    Data Science Chair

    Physics Informed Deep Learning

    Open Topics

    11/21/2024 | Physics & Deep Learning, Ecosystems

    Spherical Embeddings or Spherical Fourier Neural Operators

    Spherical Harmonics by Inigo.quilez, licensed under CC BY-SA 3.0, via Wikimedia Commons, (https://commons.wikimedia.org/wiki/File:Spherical_Harmonics.png)
    Although our planet is a sphere and therefor all weather and climate processes operate on sphere, Deep Learning Weather Models very commonly operate on different rectangular projections of the sphere. This introduces increasingly… more
    11/13/2024 | Physics & Deep Learning, Ecosystems

    Meteorological Downscaling Using Remote Sensing Data

    Global numerical climate models project meteorological quantities such as temperature, humidity, pressure, etc. decades into the future under the assumption of different emission scenarios. However, due to computational… more
    11/11/2024 | Physics & Deep Learning, Ecosystems

    Resolution-Invariant Training of Deep Learning Athmospheric Models

    Athmosperic Circulation Models simulate the evolution of the state of the atmosphere and are used to generate weather forecasts or climate projections. Deep Learning has successfully been applied to learn the dynamics of the… more
    10/17/2023 | 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? more
    10/17/2023 | 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… more
    06/07/2023 | 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,… more
    06/07/2023 | 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. more
    06/07/2023 | 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. more
    06/05/2023 | 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… more