Introduction to Differentiable Programming In Hep

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Differentiable Programming In Hep Comprehensive Overview

Lukas Heinrich, TU Munich. This tutorial will cover how to optimise various aspects of analyses -- such as cuts, binning, and learned observables like neural ... In the ideal world, we describe our models with recognizable mathematical expressions and directly fit those models to large data ...

Derivatives are at the heart of scientific

Summary & Highlights for Differentiable Programming In Hep

  • Deep learning has led to encouraging successes in many challenging tasks. However, a deep neural model lacks interpretability ...
  • Jan Margeta -
  • Dimitri spittoon it is and Simon Peter Jones on
  • e-Seminar on Scientific Machine Learning Speaker: Dr. Jan Drgona (PNNL) Abstract: In this talk, we will present a
  • Nathan Simpson looks at what can make a physics analysis fully

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