function-approximation

There are 0 repository under function-approximation topic.

instant-ngp
NVlabs / instant-ngp
Instant neural graphics primitives: lightning fast NeRF and more
3d-reconstruction computer-graphics computer-vision cuda function-approximation machine-learning nerf neural-network real-time real-time-rendering realtime signed-distance-functions
Language:Cuda 17051
bgrimstad / splinter
Library for multivariate function approximation with splines (B-spline, P-spline, and more) with interfaces to C++, C, Python and MATLAB
b-splines splines function-approximation interpolation p-spline python c-plus-plus smoothing
Language:C++ 439
polatory / polatory
Fast radial basis function interpolation and kriging for large scale data
interpolation surface-reconstruction kriging rbf spline regression radial-basis-function cpp approximation function-approximation splines smoothing geostatistics surface-modeling kernel-methods python astronomy astrophysics geology geophysics
Language:C++ 181
jipolanco / BSplineKit.jl
A collection of B-spline tools in Julia
b-splines function-approximation galerkin collocation basis-recombination splines julia interpolation
Language:Julia 62
iamjagdeesh / Artificial-Intelligence-Pac-Man
CSE 571 Artificial Intelligence
artificial-intelligence a-star-search uniform-cost-search depth-first-search breadth-first-search greedy-search neural-networks minimax-algorithm alpha-beta-pruning expectimax reinforcement-learning value-iteration q-learning epsilon-greedy policy-iteration function-approximation particle-filter-tracking deep-reinforcement-learning
Language:Python 52
nymath / torchqtm
TorchQuantum is a backtesting framework that integrates the structure of PyTorch and WorldQuant's Operator for efficient quantitative financial analysis.
alpha-model deep-learning function-approximation quantitative-finance
Language:Cython 48
rldotai / rl-algorithms
Reinforcement learning algorithms
reinforcement-learning-algorithms reinforcement-learning algorithm rl-algorithms linear-function-approximation function-approximation
Language:Python 41
rdeits / AdaptiveDistanceFields.jl
Adaptively sampled distance fields in Julia
julia signed-distance-field geometry function-approximation
Language:Jupyter Notebook 33
floswald / Tasmanian.jl
Julia Wrapper to the Tasmanian library
function-approximation julialang julia-package tasmanian
Language:Julia 32
BasisFunctionExpansions.jl
baggepinnen / BasisFunctionExpansions.jl
Basis Function Expansions for Julia
approximation linear-regression time-series-analysis function-expansion function-approximation julia-package
Language:Julia 27
flatironinstitute / baobzi
An adaptive fast function approximator based on tree search
julia python high-performance-computing approximation c cpp matlab fortran scientific-computing eigen msgpack cmake function-approximation
Language:C++ 17
JuliaApproximation / CompactBases.jl
Julia library for function approximation with compact basis functions
finite-differences fe-dvr fedvr b-splines function-approximation quasi-arrays
Language:Julia 17
leolellisr / poke_RL
Code repository with classical reinforcement learning and deep reinforcement learning methods for Pokémon battles in Pokémon Showdown.
pokemon reinforcement-learning monte-carlo sarsa-lambda qlearning function-approximation game dqn double-dqn ppo ppo2 deep-reinforcement-learning deep-rl reinforce pokemon-showdown
Language:Jupyter Notebook 16
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)
sciml scientific-machine-learning pseudospectral fourier chebyshev function-approximation partial-differential-equation
Language:Julia 14
timbmg / easy21-rl
Easy21 assignment from David Silver's RL Course at UCL
function-approximation monte-carlo reinforcement-learning reinforcement-learning-excercises rl sarsa sarsa-lambda
Language:Python 11
NormalHermiteSplines.jl
IgorKohan / NormalHermiteSplines.jl
Multivariate Normal Hermite-Birkhoff Interpolating Splines in Julia
interpolation multivariate splines hermite-splines normal-splines rkhs approximation rbf function-approximation hermite-birkhoff matern-kernel
Language:Julia 10
Pressio / pressio-demoapps
Suite of 1D, 2D, 3D demo apps of varying complexity with built-in support for sample mesh and exact Jacobians
euler-equations compressible-flows numerical-methods weno-schemes hyper-reduction advection pybind11 riemann-problem finite-volume hydrodynamics sample-mesh shock-capturing snl-mini-apps jacobian-matrix function-approximation reaction-diffusion snl-applications python3 eigen-library cpp17
Language:C++ 9
shuvoxcd01 / GridMind
A library of reinforcement learning (RL) algorithms.
monte-carlo-methods reinforcement-learning temporal-differencing-learning function-approximation n-step evolutionary-reinforcement-learning
Language:Python 8
Breakend / CMACvTileCode
tensorflow cmac mlp tile-coding reinforcement-learning function-approximation
Language:Python 7
GeorgianBadita / Genetic-Programming-Function-Approximation
Python framework to approximate mathemtical functions
genetic-algorithm genetic-programming function-approximation
Language:Jupyter Notebook 7
YNU-NakataLab / X-KAN
X-KAN: Optimizing Local Kolmogorov-Arnold Networks via Evolutionary Rule-Based Machine Learning
divide-and-conquer evolutionary-rule-based-machine-learning function-approximation kolmogorov-arnold-networks learning-classifier-systems xcsf
Language:Python 6
AI4LIFE-GROUP / lfa
Local function approximation (LFA) framework, NeurIPS 2022
explainability explainable-ai explainable-ml faithful-explanation function-approximation interpretability
Language:Python 5
Elktrn / 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
regression regressor tensorflow2 gradient-descent-algorithm function-approximator function-approximation
Language:Jupyter Notebook 5
nimanaqavi / Verilog-MathFunctions
A Verilog-based system for approximating mathematical functions (exp, sin, cos, ln) using Taylor/Maclaurin series, suitable for FPGA implementation and simulation.
verilog digital-design fpga function-approximation hardware-implementation mathematical-functions taylor-series numerical-methods exp-function sin-cos-function verilog-project ln-function
Language:Verilog 5
thomberg1 / UniversalFunctionApproximation
Universal Function Approximation by Neural Nets
neural-network function-approximation pytorch
Language:Jupyter Notebook 5
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.
tensorflow sympy sympy-library filters deep-learning function-approximation extrapolation
Language:Jupyter Notebook 5
harmanpreet93 / reinforcement-learning
Reinforcement Learning algorithms
bandit function-approximation q-learning reinforcement-learning rl sarsa td-learning
Language:Jupyter Notebook 4
PhuongLe / deep-q-learning-robot
An implementation of Reinforcement Learning using the Q-Learning algorithm and Function Approximation with Backpropagation Neural Network.
machine-learning reinforcement-learning neural-network q-learning sarsa function-approximation
Language:Java 4
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.
gradient-descent neural-network backpropagation function-approximation
Language:Jupyter Notebook 4
YasinRezvani / Fourier_Series_Animation
This project is a simple animation of Fourier series, approximating a function using a sum of sine and cosine functions.
animation mathematics matplotlib numpy python computional-mathematics data-visualization digital-signal-processing fourier-series function-approximation mathematical-modelling signal-analysis signal-processing rezvani yasin yasin-rezvani yasin-rezvani-github
Language:Python 4
multi-threading
Gyakobo / multi-threading
This project was made to showcase a sample example of muli-threading in the C programming language.
c function-approximation integrals integration multithreading number-pi parallel-computing
Language:C 3
HarryZhangHH / DPRL
Course given at the MSc CS @VU
function-approximation reinforcement-learning
Language:Jupyter Notebook 3
isthatyoung / MLP-Function-Approximation
An implementation of multilayer perceptron(MLP) on function approximation.
mlp-networks function-approximation
Language:Python 3
LMesaric / Seminar-FER-2019
Seminar project at FER led by Assistant Professor Marko Čupić
seminar python python3 genetic-algorithm evolutionary-algorithms function-approximation approximation numpy sympy matplotlib deap paper latex
Language:TeX 3
SaiVinay007 / Reinforcement-Learning-CS6700
Course work of Reinforcement-Learning-CS6700
reinforcement-learning sarsa q-learning dqn-tensorflow policy-gradient function-approximation hierarchical-reinforcement-learning multi-armed-bandits open-ai-gym puddle-world four-rooms monte-carlo gym-environment
Language:Jupyter Notebook 3
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
machine-learning sentence-tokenizer cosine-distance function-approximation polynomial-calculator function-optimization function-minimization
Language:Python 3

function-approximation

NVlabs / instant-ngp

bgrimstad / splinter

polatory / polatory

jipolanco / BSplineKit.jl

iamjagdeesh / Artificial-Intelligence-Pac-Man

nymath / torchqtm

rldotai / rl-algorithms

rdeits / AdaptiveDistanceFields.jl

floswald / Tasmanian.jl

baggepinnen / BasisFunctionExpansions.jl

flatironinstitute / baobzi

JuliaApproximation / CompactBases.jl

leolellisr / poke_RL

SciML / DiffEqApproxFun.jl

timbmg / easy21-rl

IgorKohan / NormalHermiteSplines.jl

Pressio / pressio-demoapps

shuvoxcd01 / GridMind

Breakend / CMACvTileCode

GeorgianBadita / Genetic-Programming-Function-Approximation

YNU-NakataLab / X-KAN

AI4LIFE-GROUP / lfa

Elktrn / tensorflow-2.0-simple-linear-regression-whitout-keras

nimanaqavi / Verilog-MathFunctions

thomberg1 / UniversalFunctionApproximation

vasisthasinghal / Learning-Equations-of-a-Dynamical-System

harmanpreet93 / reinforcement-learning

PhuongLe / deep-q-learning-robot

shiivashaakeri / Neural-Network-Gradient-Descent-From-Scratch

YasinRezvani / Fourier_Series_Animation

Gyakobo / multi-threading

HarryZhangHH / DPRL

isthatyoung / MLP-Function-Approximation

LMesaric / Seminar-FER-2019

SaiVinay007 / Reinforcement-Learning-CS6700

sichkar-valentyn / Machine_Learning_in_Python