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.

A collection of B-spline tools in Julia

CSE 571 Artificial Intelligence

Reinforcement learning algorithms

Julia Wrapper to the Tasmanian library

Adaptively sampled distance fields in Julia

Basis Function Expansions for Julia

TorchQuantum is a backtesting framework that integrates the structure of PyTorch and WorldQuant's Operator for efficient quantitative financial analysis.

Julia library for function approximation with compact basis functions

An adaptive fast function approximator based on tree search

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

Multivariate Normal Hermite-Birkhoff Interpolating Splines in Julia

Easy21 assignment from David Silver's RL Course at UCL

Python framework to approximate mathemtical functions

Simple linear regressor that tries to approximate a simple function deployed in Tensorflow 2.0 without Keras

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

Universal Function Approximation by Neural Nets