Instant neural graphics primitives: lightning fast NeRF and more
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Updated
Feb 21, 2022 - Cuda
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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
Basis Function Expansions for Julia
Julia library for function approximation with compact basis functions
A collection of B-spline tools in Julia
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
Universal Function Approximation by Neural Nets
Reinforcement Learning algorithms
Course work of Reinforcement-Learning-CS6700
Seminar project at FER led by Assistant Professor Marko Čupić
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.
MLP network for approximating functions: implementation and experiments (in Polish)
Python framework to approximate mathemtical functions
Assignments and Reading Material for RL Course
Practical experiments on Machine Learning in Python. Processing of sentences and finding relevant ones, approximation of function with polynomials, function optimization
An implementation of multilayer perceptron(MLP) on function approximation.
Approximation of mixing different gaussian distribution with Self-organizing Map(SoM) and Radial Basis Function(RBF)
Neural Network from scratch (Multilayer Perceptron) with modular implementation
Simple linear regressor that tries to approximate a simple function deployed in Tensorflow 2.0 without Keras
My Machine Learning course projects
This is a repository for Coursera Reinforcement Learning Course Notebook ,, these consist of my solutions. Feel Free to take a look , if you are stuck in Course and suggest corrections, if you find any mistake. Also Useful if you are looking for an implementation of RL-Algorithms. ** NOTE THESE NOTEBOOKS DON'T WORK AS THEY DO NOT CONTAIN UTILITY FILES WHICH ARE AVAILABLE ONLY ON COURSERA.
An implementation of Reinforcement Learning using the Q-Learning algorithm and Function Approximation with Backpropagation Neural Network.
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