Name: Christian Kragh Jespersen
Type: User
Company: Department of Astrophysics, Princeton University
Bio: Graduate student at Princeton (Astrophysics). Optimizing information gain from data with ML.
Twitter: astrockragh
Blog: astrockragh.github.io
Christian Kragh Jespersen's Projects
My website
For Haugbølle computational astrophysics course
All the weird stuff I've done to get to help with COSMOS
Cosmic Variance Notebooks/Python in cosmic_variance
Tutorials for the KITP Galevo23 program
Using t-SNE to classify GRBs from the Swift catalogue, https://arxiv.org/pdf/2005.13554.pdf
Estimating galaxy-halo properties using graph neural networks
Collection of ML methods to analyze and reconstruct particle paths
Using Graph Neural Networks to regress baryonic properties directly from full dark matter merger trees.
Python package based on the IDL code released with the Cosmic Variance Cookbook of Moster et al. (2010)
RAGNAR, the Resolution Adaptive Generator of Nocturnal Airglow Radiation, creates line lists of sky emission lines with unprecedented accuracy for wavelength calibration of spectrographs and for robust atmospheric study.
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