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| Nöh, Katharina k.noeh@fz-juelich.de | IBG-1: Biotechnology, Modeling and Simulation Group | Image segmentation with DL (U-Nets) | Large-scale microscopic images from time-lapse microscopy (2D, x-TB range) | Meet DL/ML experts, discuss DL solutions for specific applications |
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| Pleiter, Dirk d.pleiter@fz-juelich.de | JSC Technology Department | Architectures optimized for DL, requirements analysis | | |
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|Schiffer, Christian c.schiffer@fz-juelich.de | INM-1 Big Data Analytics Group (BDA) | Deep Learning with ConvNets, Image Segmentation, Distributed DL on HPC with TensorFlow, Unsupervised Domain Adaptation | Microscopic resolution 2D images |
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|Schultz, Martin m.schultz@fz-juelich.de | JSC-FSD | Deep Learning Timeseries and video-sequence analysis (IntelliAQ project) | Observational time series, numerical weather model data (gridded fields), geodata (gridded fields and point features | discussion forum to exchange experiences with specific architectures and methods, and to share ideas how to improve result |
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| Stadtler, Scarlet s.stadtler@fz-juelich.de | JSC Federated Systems and Data Division | Absolute Beginner (At JSC courses in ML and DL) | Meteorological four dimensional Data (space and time) | meet ML experts, possibility to discuss individual DL problems |
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| Schlottke-Lakemper, Michael m.schlottke-lakemper@fz-juelich.de | JSC/JARA SimLab Fluids & Solids | Beginner | Continuum mechanics (fluids, solids) | Meet like-minded researches & ML experts to exchange ideas, learn who to ask in case of specific problems/questions |
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|Schultz, Martin m.schultz@fz-juelich.de | JSC-FSD | Deep Learning Timeseries and video-sequence analysis (IntelliAQ project) | Observational time series, numerical weather model data (gridded fields), geodata (gridded fields and point features | discussion forum to exchange experiences with specific architectures and methods, and to share ideas how to improve result |
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| Schober, Martin m.schober@fz-juelich.de | INM-1 Fiber Architecture Group | Beginner | Microscopic resolution 2D and 3D images, scalar and vector valued data | |
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| Stadtler, Scarlet s.stadtler@fz-juelich.de | JSC Federated Systems and Data Division | Absolute Beginner (At JSC courses in ML and DL) | Meteorological four dimensional Data (space and time) | meet ML experts, possibility to discuss individual DL problems |
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| Ungermann, Jörn j.ungermann@fz-juelich.de | IEK-7 | Inverse Modelling, Linear Regression | 2-D and 3-D interferograms | |
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| Wagner, Christian c.wagner@fz-juelich.de | PGI-3 Molecular manipulation lab | general overview over ML principles, PCA, background on methods to combine ML and comptational chemistry, reinforcement learning with NNs | (hysteretic) scalars along (x,y,z), trajectories, computational, chemistry data, scalar time series | easy access to ML expertise, possibility to discuss (and potentially solve) individual ML problems / tasks at detailed level, potentially in the frame of a collaboration |
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| Wenzel, Susanne s.wenzel@fz-juelich.de | INM-1 Big Data Analytics Group (BDA) | Markov Marked Point Processes, rjMCMC | | |
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