Differentiable Programming In Hep

Summary

Behind Every Great Deep Learning Framework Is An Even Greater This tutorial will cover how to optimise various aspects of analyses -- such as cuts, binning, and learned observables neural ... In the ideal world, we describe our models with recognizable mathematical expressions and directly fit those models to large data ... This talk was presented as part of JuliaCon 2021. Abstract: Deep learning has grown steadily and there has been rising interest ... itsatcuny.org/calendar/quantum-inspired-machine-learning Lei Wang, Institute of Physics, Chinese Academy of Sciences ... Want to train programs to optimize themselves? Accelerating Scientific Machine Learning with Automatic Friday Talks - 20260320 fridaytalks.github.io Speaker: A. René Geist andregeist.github.io/ Title: SoftJAX & SoftTorch: ... STAMPS Workshop on Neural Simulation-Based Inference, October 5, 2025 Speaker: Patrick Heimbach (University of Texas at ... Derivatives are at the heart of scientific In Fall 2020 and Spring 2021, this was MIT's 18.337J/6.338J: Parallel Computing and Scientific Machine Learning course. According to Max Haughton, the calculation of gradients is a way to understand the universe. For the entire history of computing, ...