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@Photon-AI-Research

AI for Future Photon Science

We ❤️ Photons

Welcome to AI for Future Photon Science 👋

🙋‍♀️ We contribute to the understanding of fundamental properties in photon science like what happens once a Laser interacts with matter by machine learning. From an experiental point of view, we employ very brilliant beams of Photons (X-rays) to image very small-scale or ultra-fast processes. The corresponding problems in computational imaging are approached by ML, too 😀

🚀 Our ML research is converging into a digital twin of Laser-driven particle accelerators which comprises of surrogate modeling, uncertainty quantification / outlier detection and neural solvers

🚀 We are also solving Inverse X-ray imaging problems by generative models like normalising flows for fast understanding of experimental data from instruments like HIBEF situated at large-scale facilities EuropeanXFEL, DESY, etc.

🌈 Feel free to message Jeffrey if you are interested in contributing to our research 😀

👩‍ Please find a more detailed description of our projects and publications here: photon-ai-research.github.io

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  1. NeuralSolvers NeuralSolvers Public

    Neural network based solvers for partial differential equations and inverse problems 🌌. Implementation of physics-informed neural networks in pytorch.

    Python 141 46

  2. NF4IP NF4IP Public

    Normalising flows for Inverse Problems is a framework providing all means for data-driven solutions to inverse (imaging) problems.

    Python 6

  3. ClassifyInjectionRadiation_by_NF4IP ClassifyInjectionRadiation_by_NF4IP Public

    Python 1 1

  4. GISAXS-analysis GISAXS-analysis Public

    Forked from maxxxzdn/gisaxs-reconstruction

    ML-based reconstruction of GISAXS data

    Jupyter Notebook

  5. Physics-Based-Deep-Learning Physics-Based-Deep-Learning Public

    Forked from thunil/Physics-Based-Deep-Learning

    Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond

    3 1

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