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Reporting module
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Simulation module
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Visualization module
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Goal of the project is to provide several algorithms to smooth the trajectories of persons a) to correct data uncertainty b) to remove swaying of heads and get paths of the real main direction of movement
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Framework for simulating pedestrians with state of the art models.
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Samples and documentation for the "Getting started with ML/DL on Supercomputers" tutorial.
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High-level Fortran and C wrappers for D.E.Shaw Research's random123
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method to define and switch between multiple desktop profiles
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Portable "minimal" Emacs configuration. Works on Linux and Mac.
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Framework for the Pre-processing of fire simulation results for JPScore
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Useful links for creating publication quality figures using python
