Library for multivariate function approximation with splines (B-spline, P-spline, and more) with interfaces to C++, C, Python and MATLAB
-
Updated
Feb 15, 2023 - C++
#
function-approximation
Here are 56 public repositories matching this topic...
Fast radial basis function interpolation and kriging for large scale data
python cpp astronomy interpolation regression approximation geophysics astrophysics surface-reconstruction smoothing splines spline kernel-methods geology geostatistics kriging function-approximation surface-modeling radial-basis-function rbf
-
Updated
Sep 4, 2025 - C++
A collection of B-spline tools in Julia
interpolation julia splines galerkin function-approximation collocation b-splines basis-recombination
-
Updated
Aug 20, 2025 - Julia
CSE 571 Artificial Intelligence
reinforcement-learning deep-reinforcement-learning q-learning artificial-intelligence neural-networks epsilon-greedy breadth-first-search alpha-beta-pruning depth-first-search minimax-algorithm policy-iteration value-iteration function-approximation expectimax particle-filter-tracking uniform-cost-search greedy-search a-star-search
-
Updated
Jan 3, 2018 - Python
TorchQuantum is a backtesting framework that integrates the structure of PyTorch and WorldQuant's Operator for efficient quantitative financial analysis.
-
Updated
Jul 13, 2023 - Cython
Reinforcement learning algorithms
algorithm reinforcement-learning reinforcement-learning-algorithms function-approximation rl-algorithms linear-function-approximation
-
Updated
Feb 27, 2019 - Python
Adaptively sampled distance fields in Julia
-
Updated
Apr 19, 2023 - Jupyter Notebook
Julia Wrapper to the Tasmanian library
-
Updated
Jul 28, 2025 - Julia
Basis Function Expansions for Julia
linear-regression approximation julia-package function-approximation time-series-analysis function-expansion
-
Updated
Apr 6, 2023 - Julia
Julia library for function approximation with compact basis functions
-
Updated
Mar 9, 2024 - Julia
The tools for proper interactions between ApproxFun.jl and DifferentialEquations.jl for pseudospectiral partial differential equation discretizations in scientific machine learning (SciML)
fourier function-approximation chebyshev pseudospectral scientific-machine-learning partial-differential-equation sciml
-
Updated
Nov 30, 2020 - Julia
Easy21 assignment from David Silver's RL Course at UCL
reinforcement-learning monte-carlo sarsa rl function-approximation reinforcement-learning-excercises sarsa-lambda
-
Updated
Apr 29, 2018 - Python
Multivariate Normal Hermite-Birkhoff Interpolating Splines in Julia
interpolation approximation multivariate splines rkhs function-approximation rbf normal-splines matern-kernel hermite-splines hermite-birkhoff
-
Updated
Apr 20, 2021 - Julia
Suite of 1D, 2D, 3D demo apps of varying complexity with built-in support for sample mesh and exact Jacobians
python3 cpp17 reaction-diffusion finite-volume numerical-methods hydrodynamics euler-equations weno-schemes eigen-library function-approximation advection compressible-flows pybind11 riemann-problem shock-capturing jacobian-matrix sample-mesh hyper-reduction snl-applications snl-mini-apps
-
Updated
Sep 9, 2025 - C++
-
Updated
Mar 31, 2017 - Python
Python framework to approximate mathemtical functions
-
Updated
Jun 13, 2020 - Jupyter Notebook
X-KAN: Optimizing Local Kolmogorov-Arnold Networks via Evolutionary Rule-Based Machine Learning
learning-classifier-systems function-approximation divide-and-conquer xcsf evolutionary-rule-based-machine-learning kolmogorov-arnold-networks
-
Updated
Jul 4, 2025 - Python
Universal Function Approximation by Neural Nets
-
Updated
Sep 1, 2018 - Jupyter Notebook
Local function approximation (LFA) framework, NeurIPS 2022
function-approximation interpretability explainable-ai explainable-ml explainability faithful-explanation
-
Updated
Feb 6, 2023 - Python
Reinforcement Learning algorithms
-
Updated
Apr 7, 2020 - Jupyter Notebook
Improve this page
Add a description, image, and links to the function-approximation topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the function-approximation topic, visit your repo's landing page and select "manage topics."