Introduction to Differentiable Programming In Hep
Welcome to our comprehensive guide on Differentiable Programming In Hep. Talk from HSF/IRIS-
Differentiable Programming In Hep Comprehensive Overview
Lukas Heinrich, TU Munich. Derivatives are at the heart of scientific This tutorial will cover how to optimise various aspects of analyses -- such as cuts, binning, and learned observables like neural ...
Speaker: Dr Aidan Crilly.
Summary & Highlights for Differentiable Programming In Hep
- Jan Margeta -
- e-Seminar on Scientific Machine Learning Speaker: Dr. Jan Drgona (PNNL) Abstract: In this talk, we will present a
- In Fall 2020 and Spring 2021, this was MIT's 18.337J/6.338J: Parallel Computing and Scientific Machine Learning course.
- In the ideal world, we describe our models with recognizable mathematical expressions and directly fit those models to large data ...
- Deep learning has led to encouraging successes in many challenging tasks. However, a deep neural model lacks interpretability ...
In summary, understanding Differentiable Programming In Hep gives us a better perspective.
