A differentiable forward model and likelihood enable probabilistic inference over many spatial morphologies for the Galactic Center gamma-ray Excess using variational methods on GPUs.
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Updated constraints on two simplified dark matter models for the Galactic Center Excess leave unconstrained parameter space after applying recent multi-experiment data.
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High-dimensional inference for the $\gamma$-ray sky with differentiable programming
A differentiable forward model and likelihood enable probabilistic inference over many spatial morphologies for the Galactic Center gamma-ray Excess using variational methods on GPUs.
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Testing Viability of Benchmark Dark Matter Models for the Galactic Center Excess
Updated constraints on two simplified dark matter models for the Galactic Center Excess leave unconstrained parameter space after applying recent multi-experiment data.