Differentiable Programming In Hep Information Guide

  1. Overview of Differentiable Programming In Hep
  2. Main Features
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Overview of Differentiable Programming In Hep

Differentiable Programming in HEP News
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Main Features

Differentiable Programming in HEP News
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Recent Updates

Full The principles behind Differentiable Programming - Erik Meijer Guide
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PyHEP2022 Speeding up differentiable programming with a Computer Algebra System
PyHEP2022 Speeding up differentiable programming with a Computer Algebra System
A Tour of the differentiable programming landscape with Flux.jl | Dhairya Gandhi | JuliaCon 2021
A Tour of the differentiable programming landscape with Flux.jl | Dhairya Gandhi | JuliaCon 2021
Differentiable Programming Tensor Networks - Lei Wang
Differentiable Programming Tensor Networks - Lei Wang
Accelerating Scientific Machine Learning with Automatic Differentiable Surrogates - Ludovico Bessi
Accelerating Scientific Machine Learning with Automatic Differentiable Surrogates - Ludovico Bessi
DConf Online '22 - Differentiable Programming in D
DConf Online '22 - Differentiable Programming in D
SoftJAX & SoftTorch: Soft Differentiable Programming for Scientific Machine Learning - [@AndReGeist]
SoftJAX & SoftTorch: Soft Differentiable Programming for Scientific Machine Learning - [@AndReGeist]
Patrick Heimbach: Differentiable Programming For Hybrid Data Assimilation & Machine Learning
Patrick Heimbach: Differentiable Programming For Hybrid Data Assimilation & Machine Learning
Differentiable Programming for Modeling and Control of Dynamical Systems
Differentiable Programming for Modeling and Control of Dynamical Systems
Coarsening Optimization for Differentiable Programming
Coarsening Optimization for Differentiable Programming
Use of auto-differentiation within the ACTS toolkit (Benjamin Huth, Universität Regensburg)
Use of auto-differentiation within the ACTS toolkit (Benjamin Huth, Universität Regensburg)
Differentiable programming in action
Differentiable programming in action

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Last Updated: October 2, 2026

Final Thoughts

PyHEP2022 Analysis Optimisation with Differentiable Programming Update
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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 ... Accelerating Scientific Machine Learning with Automatic According to Max Haughton, the calculation of gradients is a way to understand the universe. For the entire history of computing, ... 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 ... e-Seminar on Scientific Machine Learning Speaker: Dr. Jan Drgona (PNNL) Abstract: In this talk, we will present a Video from Compiler Research / IRIS- Yet another example from my demonstrative project on

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