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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UNVERDICTED 2representative citing papers
Maximum-likelihood-based posterior predictive checks detect model misspecification better than event-level versions for uncertain spin tilts, but current detector sensitivity limits their power; the Gaussian Component Spins model underpredicts high spin magnitudes and overpredicts anti-aligned tilts
citing papers explorer
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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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Posterior Predictive Checks for Gravitational-wave Populations: Limitations and Improvements
Maximum-likelihood-based posterior predictive checks detect model misspecification better than event-level versions for uncertain spin tilts, but current detector sensitivity limits their power; the Gaussian Component Spins model underpredicts high spin magnitudes and overpredicts anti-aligned tilts