function-approximation
There are 67 repositories under function-approximation topic.
NVlabs/instant-ngp
Instant neural graphics primitives: lightning fast NeRF and more
bgrimstad/splinter
Library for multivariate function approximation with splines (B-spline, P-spline, and more) with interfaces to C++, C, Python and MATLAB
polatory/polatory
Fast radial basis function interpolation for large scale data
jipolanco/BSplineKit.jl
A collection of B-spline tools in Julia
iamjagdeesh/Artificial-Intelligence-Pac-Man
CSE 571 Artificial Intelligence
rldotai/rl-algorithms
Reinforcement learning algorithms
rdeits/AdaptiveDistanceFields.jl
Adaptively sampled distance fields in Julia
floswald/Tasmanian.jl
Julia Wrapper to the Tasmanian library
nymath/torchqtm
TorchQuantum is a backtesting framework that integrates the structure of PyTorch and WorldQuant's Operator for efficient quantitative financial analysis.
baggepinnen/BasisFunctionExpansions.jl
Basis Function Expansions for Julia
JuliaApproximation/CompactBases.jl
Julia library for function approximation with compact basis functions
flatironinstitute/baobzi
An adaptive fast function approximator based on tree search
SciML/DiffEqApproxFun.jl
The tools for proper interactions between ApproxFun.jl and DifferentialEquations.jl for pseudospectiral partial differential equation discretizations in scientific machine learning (SciML)
IgorKohan/NormalHermiteSplines.jl
Multivariate Normal Hermite-Birkhoff Interpolating Splines in Julia
timbmg/easy21-rl
Easy21 assignment from David Silver's RL Course at UCL
GeorgianBadita/Genetic-Programming-Function-Approximation
Python framework to approximate mathemtical functions
leolellisr/poke_RL
Code repository with classical reinforcement learning and deep reinforcement learning methods for Pokémon battles in Pokémon Showdown.
Pressio/pressio-demoapps
Suite of 1D, 2D, 3D demo apps of varying complexity with built-in support for sample mesh and exact Jacobians
MohammadAsadolahi/tensorflow-2.0-simple-linear-regression-whitout-keras
Simple linear regressor that tries to approximate a simple function deployed in Tensorflow 2.0 without Keras
vasisthasinghal/Learning-Equations-of-a-Dynamical-System
The focus of function approximation problems has been on identifying some suitable function without attempting to gain insight into the mechanism of the system. The performance of the model boils down to interpolation. But, in a more realistic setting, we expect test data from outside the distribution of the training set. To better extrapolate to unseen domains, it is essential to learn the correct underlying equations of the system. The Equation Learner (EQL) Network attempts to achieve this task.
harmanpreet93/reinforcement-learning
Reinforcement Learning algorithms
thomberg1/UniversalFunctionApproximation
Universal Function Approximation by Neural Nets
akiss-xyz/certainpy
A short and sweet library handling uncertainty in calculations. Can use both standard, probabilistic uncertainties and maximal uncertainties for arbitrary functions over arbitrary variables.
HarryZhangHH/DPRL
Course given at the MSc CS @VU
LMesaric/Seminar-FER-2019
Seminar project at FER led by Assistant Professor Marko Čupić
PhuongLe/deep-q-learning-robot
An implementation of Reinforcement Learning using the Q-Learning algorithm and Function Approximation with Backpropagation Neural Network.
SaiVinay007/Reinforcement-Learning-CS6700
Course work of Reinforcement-Learning-CS6700
shiivashaakeri/Neural-Network-Gradient-Descent-From-Scratch
This project is a simple implementation of a neural network with gradient descent optimization from scratch. The goal of this project is to demonstrate how a neural network works and how the gradient descent algorithm can be used to optimize its parameters.
YasinRezvani/Fourier_Series_Animation
This project is a simple animation of Fourier series, approximating a function using a sum of sine and cosine functions.
AdamRajfer/mlp-from-scratch
MLP network for approximating functions: implementation and experiments
AI4LIFE-GROUP/lfa
Local function approximation (LFA) framework, NeurIPS 2022
Arminkhayati/Machine_learning_lec
My Machine Learning course projects
Sagarnandeshwar/On_Policy_And_Off_Policy_Reinforcement_Learning
Reinforcement Learning (COMP 579) Project
sichkar-valentyn/Machine_Learning_in_Python
Practical experiments on Machine Learning in Python. Processing of sentences and finding relevant ones, approximation of function with polynomials, function optimization
Souritra-Garai/Neural-Networks
A generic implementation of multi layer perceptron neural networks, including some visual tools. Contains example of using the neural network classes for function approximation.