Using automatic differentiation as a general framework for ptychographic reconstruction (Journal Article) | DOE PAGES
Deep Learning Library From Scratch 4: Automatic differentiation - DEV Community
Automatic differentiation - Wikiwand
Automatic Differentiation Background - MATLAB & Simulink
Automatic Differentiation Part 1: Understanding the Math - PyImageSearch
Gabriel Peyré on Twitter: "Reverse mode automatic-differentiation is based on a « backward » (adjoint) chain rule. https://t.co/SXoF9PxtDX https://t.co/xJJ2VEdIEY" / Twitter
Reverse-mode automatic differentiation from scratch, in Python | sidsite
Automatic Differentiation, Explained | by Chi-Feng Wang | Towards Data Science
Automatic differentiation | fmin.xyz
A Gentle Introduction to Automatic Differentiation | by Pablo Monteagudo Lago | Towards AI
Automatic differentiation from scratch | Emilio's Blog
Automatic Differentiation with torch.autograd — PyTorch Tutorials 2.0.0+cu117 documentation
Automatic Differentiation Using Gradient Tapes - Gowri Shankar
Automatic Differentiation in Quantum Chemistry with Applications to Fully Variational Hartree–Fock | ACS Central Science
PyTorch Basics: Understanding Autograd and Computation Graphs
A Functional Tour of Automatic Differentiation
![PDF] Automatic differentiation in machine learning: a survey | Semantic Scholar](https://d3i71xaburhd42.cloudfront.net/da118b8aa99699edd7609fbbd081d5b93bc2e87b/3-Figure1-1.png "PDF] Automatic differentiation in machine learning: a survey | Semantic Scholar")
PDF] Automatic differentiation in machine learning: a survey | Semantic Scholar
What is Automatic Differentiation? - YouTube
On the Equivalence of Forward Mode Automatic Differentiation and Symbolic Differentiation | Semantic Scholar
Inverse Hamiltonian design by automatic differentiation | Communications Physics
Automatic Differentiation - an overview | ScienceDirect Topics
Automatic Differentiation: Applications, Theory, and Implementations (Lecture Notes in Computational Science and Engineering, 50): Bücker, H. Martin, Corliss, George, Hovland, Paul, Naumann, Uwe, Norris, Boyana: 9783540284031: Amazon.com: Books
Using TensorFlow and GradientTape to train a Keras model - PyImageSearch
