sadET
Simple Automatic Differentiation (using) Expression Templates (by dkaramit)
TemporalSetInversion
Reference implementation for "Temporal Set Inversion for Animated Implicits" (SIGGRAPH 2023) (by cryvosh)
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sadET | TemporalSetInversion | |
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1 | 1 | |
1 | 10 | |
- | - | |
6.6 | 5.3 | |
about 1 month ago | 8 months ago | |
C++ | C++ | |
MIT License | GNU General Public License v3.0 only |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
sadET
Posts with mentions or reviews of sadET.
We have used some of these posts to build our list of alternatives
and similar projects.
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Assign expression-template to variable in C++
Then, each expression should carry enough information that you can call different member functions, such as derivative for their derivative, or conjugate to take its complex conjugate, etc. Now, the conjugate (and derivative) member function should somehow inherit its behaviour from the sub expressionss. You only need to define what conjugate means for the Number class, and then all other expressions, just apply this function to its sub expressions, until a Number is reached. I am not sure if this is detailed enough, but I apply this logic here. In this piece of code, I am using ETs to that define expressions, and then use these expressions to take their derivatives. This is an autodiff library (without dual numbers), which works well, but it suffers from the the problem; can't find a way to assign and reassign variables to expressions.
TemporalSetInversion
Posts with mentions or reviews of TemporalSetInversion.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-07.
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How do you break into the graphics engineering industry?
This project uses some state-of-the-art techniques: https://github.com/cryvosh/TemporalSetInversion
What are some alternatives?
When comparing sadET and TemporalSetInversion you can also consider the following projects:
Zygote.jl - 21st century AD
FastAD - FastAD is a C++ implementation of automatic differentiation both forward and reverse mode.
autodiff - automatic differentiation made easier for C++
curv - a language for making art using mathematics
LearnOpenGL - Code repository of all OpenGL chapters from the book and its accompanying website https://learnopengl.com
control-toolbox - The Control Toolbox - An Open-Source C++ Library for Robotics, Optimal and Model Predictive Control
pinocchio - A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives