Birs- 18w5095: DM-Stat: Statistical Challenges in the Search for Dark Matter
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Title: OVERVIEW: Dark matter
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Title: OVERVIEW: Model selection, including Bayesian and Frequency perspectives
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Title: OVERVIEW: Statistical Learning
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Title: Simulation inversion: use machine learning to predict model parameters from observables
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Title: OVERVIEW: Direct searches for dark matter
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Title: Dark matter model comparison
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Title: Problems of scanning a large parameter space
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Title: OVERVIEW: Dark matter structure and simulations
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Title: The impact of Galactic astrophysical uncertainties on the reconstruction of DM properties
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Title: Statistical challenges in substructure lensing
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Title: Probing particle dark matter with Gaia DR1
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Title: OVERVIEW: statistics in indirect detection
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Title: Characterizing point source populations with non-Poissonian template fitting
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Title: Enhancing the sensitivity to dark matter signatures in the very-high-energy gamma-ray band through machine learning
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Title: WIMP or non-WIMP? Thermal DM or non-thermal DM? The question to ask before global analysis
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Title: Fast Forecasting for Counting Experiments
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Title: Extragalactic and Galactic Searches for Dark Matter Annihilation
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Title: OVERVIEW: Non-Exchangeable Hierarchical Bayes Models for Synthesizing Disparate Information
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Title: Comparing non-nested models by Testing One Hypothesis Multiple times
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Title: Euclideanized signals: facilitating pheno-focused model exploration
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