
SelfCalibrating the LookElsewhere Effect: Fast Evaluation of the Statistical Significance Using Peak Heights
In experiments where one searches a large parameter space for an anomaly...
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Unsupervised indistribution anomaly detection of new physics through conditional density estimation
Anomaly detection is a key application of machine learning, but is gener...
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Learning effective physical laws for generating cosmological hydrodynamics with Lagrangian Deep Learning
The goal of generative models is to learn the intricate relations betwee...
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The lookelsewhere effect from a unified Bayesian and frequentist perspective
When searching over a large parameter space for anomalies such as events...
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Sliced Iterative Generator
We introduce the Sliced Iterative Generator (SIG), an iterative generati...
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Probabilistic AutoEncoder
We introduce the Probabilistic AutoEncoder (PAE), a generative model wi...
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Normalizing Constant Estimation with Gaussianized Bridge Sampling
Normalizing constant (also called partition function, Bayesian evidence,...
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Uncertainty Quantification with Generative Models
We develop a generative modelbased approach to Bayesian inverse problem...
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Generative Learning of Counterfactual for Synthetic Control Applications in Econometrics
A common statistical problem in econometrics is to estimate the impact o...
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Posterior inference unchained with EL_2O
Statistical inference of analytically nontractable posteriors is a diff...
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Uros Seljak
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