function-approximation

Instant neural graphics primitives: lightning fast NeRF and more

Library for multivariate function approximation with splines (B-spline, P-spline, and more) with interfaces to C++, C, Python and MATLAB

Fast, memory-efficient 3D spline interpolation and global kriging, via RBF (radial basis function) interpolation.

CSE 571 Artificial Intelligence

Reinforcement learning algorithms

Julia Wrapper to the Tasmanian library

Adaptively sampled distance fields in Julia

A collection of B-spline tools in Julia

Basis Function Expansions for Julia

Julia library for function approximation with compact basis functions

The tools for proper interactions between ApproxFun.jl and DifferentialEquations.jl for pseudospectiral partial differential equation discretizations in scientific machine learning (SciML)

An adaptive fast function approximator based on tree search

Multivariate Normal Hermite-Birkhoff Interpolating Splines in Julia

Easy21 assignment from David Silver's RL Course at UCL

Reinforcement Learning algorithms

Universal Function Approximation by Neural Nets

Python framework to approximate mathemtical functions

Suite of 1D, 2D, 3D demo apps of varying complexity with built-in support for sample mesh and exact Jacobians

Course work of Reinforcement-Learning-CS6700