3rd  MODE Workshop on Differential Programming for Experiment Design

Princeton Institute for Computational Science and Engineering

MODE (for Machine-learning Optimized Design of Experiments)

Princeton University

<p>MODE (for Machine-learning Optimized Design of Experiments) is a collaboration of physicists and computer scientists who target the use of differentiable programming in design optimization of detectors for particle physics applications, extending from fundamental research at accelerators, in space, and in nuclear physics and neutrino facilities, to industrial applications employing the technology of radiation detection.</p><p>Our aim to develop modular, customizable, and scalable, fully differentiable pipelines for the end-to-end optimization of articulated objective functions that model in full the true goals of experimental particle physics endeavours, to ensure optimal detector performance, analysis potential, and cost-effectiveness.</p>

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3rd MODE Workshop on Differential Programming for Experiment Design

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3rd MODE Workshop on Differential Programming for Experiment Design

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