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08/31/2023
Branches of a Tree: Taking Derivatives of Programs with Discrete and Branching Randomness in High Energy Physics
We propose to apply several gradient estimation techniques to enable the...
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06/21/2023
Hierarchical Neural Simulation-Based Inference Over Event Ensembles
When analyzing real-world data it is common to work with event ensembles...
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03/03/2023
Configurable calorimeter simulation for AI applications
A configurable calorimeter simulation for AI (COCOA) applications is pre...
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09/30/2022
FAIR for AI: An interdisciplinary, international, inclusive, and diverse community building perspective
A foundational set of findable, accessible, interoperable, and reusable ...
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03/24/2022
Learning Optimal Test Statistics in the Presence of Nuisance Parameters
The design of optimal test statistics is a key task in frequentist stati...
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03/10/2022
neos: End-to-End-Optimised Summary Statistics for High Energy Physics
The advent of deep learning has yielded powerful tools to automatically ...
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02/28/2022
Differentiable Matrix Elements with MadJax
MadJax is a tool for generating and evaluating differentiable matrix ele...
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03/03/2021
Distributed statistical inference with pyhf enabled through funcX
In High Energy Physics facilities that provide High Performance Computin...
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07/08/2019
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
Probabilistic programming languages (PPLs) are receiving widespread atte...
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07/20/2018
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
We present a novel framework that enables efficient probabilistic infere...
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07/08/2018
Machine Learning in High Energy Physics Community White Paper
Machine learning is an important research area in particle physics, begi...
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12/21/2017
Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators
We consider the problem of Bayesian inference in the family of probabili...
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04/18/2017