#
differentiation
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automatic differentiation made easier for C++
automatic-differentiation
derivatives
auto-differentiation
differentiation
autodiff
numerical-derivation
autodifferentiation
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May 11, 2022 - C++
Open
Logo for Interactive
WhiteBlackGoose
commented
Dec 3, 2021
The package I want to suggest the idea to: AngouriMath.Interactive
The current logo includes Jupyter logo which is incorrect (since you can use that pkg in VSC Notebooks or in console etc.).
[Here](https://drive.google.com/file/d/1Y8TwuEjL0-YO2DCE6c_qs8TrhGJES_tL/view?usp=sharing
Minor bug
Minor bugs that don't affect the overall computations
Proposal
Contribute to the project by proposing some improvements
Area: Interactive
The issue is related to the AngouriMath.Interactive package
up-for-grabs
Issues which don't require internal knowledge to close so can be completed by outside contributors
a symbolic math expression evaluator for javascript
javascript
latex
integration
calculus
algebra
math
solver
equation
symbolic
solve-equations
fraction
expressions
differentiation
fractions
substitutions
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May 1, 2022 - JavaScript
Transparent calculations with uncertainties on the quantities involved (aka "error propagation"); calculation of derivatives.
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Oct 27, 2021 - Python
parth-07
commented
Apr 30, 2022
Differentiation of constexpr and consteval functions should produce constexpr and consteval functions respectively. Clad supports differentiation of constexpr and consteval functions with this expected behaviour, but we currently do not have any test for it.
Source Code Generation for Automatic Differentiation using Operator Overloading
c-plus-plus
latex
automatic-differentiation
jit
mathml
dae
differentiation
algorithmic-differentation
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Aug 28, 2021 - C++
Single cell trajectory detection
markov-chain
dimensionality-reduction
scrna-seq
trajectory-generation
diffusion-maps
differentiation
manifold-learning
single-cell-genomics
cell-fate-transitions
scrna-seq-analysis
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Dec 15, 2021 - Jupyter Notebook
Deep.Net machine learning framework for F#
machine-learning
deep-learning
fsharp
dotnet
gpu
cuda
gpu-acceleration
ndarray
tensor
gpu-computing
differentiation
symbolic-computation
symbolic-execution-engine
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Jun 25, 2019 - F#
c-sharp
parsing
optimization
simplification
calculations
derivative
rational-numbers
il-optimizations
parsing-math-expressions
differentiation
il
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Nov 29, 2020 - C#
Backpropagate derivatives through the Cholesky decomposition
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May 30, 2020 - Fortran
A simple cross platform .NET API for Intel MKL
integration
cross-platform
math
optimization
matrix
linear-algebra
root-finding
minimum
differentiation
mkl
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Mar 8, 2022 - C#
Modern Fortran Numerical Differentiation Library
optimization
numerical-methods
finite-differences
differentiation
graph-coloring
numerical-differentiation
sparsity-optimization
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May 2, 2022 - Fortran
FastAD is a C++ implementation of automatic differentiation both forward and reverse mode.
macos
linux
math
automatic-differentiation
derivatives
cpp17
auto-differentiation
differentiation
autodiff
autodifferentiation
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Jul 10, 2021 - C++
Programming language for symbolic computation with unusual combination of pattern matching features: Tree patterns, associative patterns and expressions embedded in patterns.
html
programming-language
json
natural-language-processing
computer-algebra
xml
pattern-matching
gcc
rosettacode
tree-structure
structured-data
language-technology
expression-evaluator
differentiation
symbolic-computation
bignumbers
semi-structured-data
epoc
unstructured-data
high-level-language
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May 7, 2022 - C
xFunc is a simple and easy to use application that allows you to build mathematical and logical expressions. It's written on C#. The library includes the code that converts strings to expressions (parser, lexer and etc.)
c-sharp
parser
parse
math
graph
nuget
graphs
logic
mathematics
analyzer
simplification
expression
complex-numbers
lexer
derivative
truth-tables
truth-table
differentiation
xfunc
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May 14, 2022 - C#
Automatic Differentiation Package for MATLAB
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Apr 14, 2020 - MATLAB
Implementing (parts of) TensorFlow (almost) from Scratch
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Jul 7, 2017 - Python
eXpression differentiation in Julia
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Feb 8, 2020 - Julia
The original Golang library for single variable differentiation and integration.
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Aug 2, 2017 - Go
Optimal numerical differentiation of noisy time series data in python.
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May 13, 2022 - Python
A tutorial on how to work around ‘Mutating arrays is not supported’ error while performing automatic differentiation (AD) using the Julia package Zygote.
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Dec 9, 2020 - Jupyter Notebook
FractionalCalculus.jl: A Julia package for high performance, fast convergence and high precision numerical fractional calculus computing.
integration
algorithms
julia
differentiation
numerical
fractional-calculus
differintegral
riemann-liouville
grunwald-letnikov
caputo
matrix-discrete
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May 2, 2022 - Julia
Implementation of dual numbers for automatic differentiation of programs
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Dec 24, 2021 - Mathematica
CASprzak is a Computer Algebra System by EasyKayzey (Erez Israeli Miller and Michael Kasprzak)
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Oct 30, 2021 - Java
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Feb 21, 2017 - OCaml
Weighted least squares meshless interpolator and differentiator.
python
interpolation
numpy
cython
python3
least-squares
curve-fitting
python2
python27
python34
differentiation
numerical
meshless
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Jul 18, 2018 - Python
Savitzky-Golay differentiation filters
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Mar 26, 2018 - MATLAB
Implemented the forward mode of automatic differentiation with the help of dual numbers using Python.
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Jul 8, 2021 - Jupyter Notebook
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In operations_broadcast_test.go there are some tests that are not yet filled in. The point is to test that broadcasting works for different shapes. The semantics of broadcast probably isn't clear, so please do send me a message for anything.
This is a good first issue for anyone looking to get interested