There are 0 repository under function-approximation topic.
Instant neural graphics primitives: lightning fast NeRF and more
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
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
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
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.
Reinforcement Learning algorithms
Universal Function Approximation by Neural Nets
Code repository with classical reinforcement learning and deep reinforcement learning methods for Pokémon battles in Pokémon Showdown.
Seminar project at FER led by Assistant Professor Marko Čupić
An implementation of Reinforcement Learning using the Q-Learning algorithm and Function Approximation with Backpropagation Neural Network.
Course work of Reinforcement-Learning-CS6700
MLP network for approximating functions: implementation and experiments
Local function approximation (LFA) framework, NeurIPS 2022
My Machine Learning course projects
Many different Neural Networks in Python Language. This repository is an independent work, it is related to my 'Redes Neuronales' repo, but here I'll use only Python.
Assignments and Reading Material for RL Course
Reinforcement Learning (COMP 579) Project
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.
Practical experiments on Machine Learning in Python. Processing of sentences and finding relevant ones, approximation of function with polynomials, function optimization