Numerical Methods with Python, Numpy and Matplotlib

Overview

Numerical Bric-a-Brac

Collections of numerical techniques with Python and standard computational packages (Numpy, SciPy, Numba, Matplotlib ...).

Differential Equations

Differential Equations describe many physical systems

Notebooks
implicit_solver
GitHub
Implementation of Baraff's "Large steps in cloth simulation."
spring_integrator
Analytic solution to damped spring
poisson_solver
Diffusion problem
laplace_inpainting
Laplace inpainting to restore an image

Optimizations

Those notebooks are the core algorithms for supervised and unsupervised learning in Machine learning.

Machine Learning Notebooks
Supervised Learning
linear_regression
Linear regression from scratch
polynomial_regression
Polynomial regression from scratch
logistic_regression
Logistic regression from scratch
multiclass_classifiation
Multiclass Classification with Scikit-learn
support_vector_machine
Support Vector Machine (SVM) with Scikit-learn
Unsupervised Learning
k_means
K-means clustering from scratch
Other Notebooks
multivariable_optimizations
Multivariable Optimizations (Gradient Descent and Newton's methods)

Linear Algebra

Standard linear algebra algorithms

Notebooks
inverse_kinematic
Inverse kinematics using least square methods to solve the ill-posed problem
radial_basis_kernels
Interpolation with Radial Basis Functions (RBFs)

Graph Theory

Part of discrete mathematics, graph theory is the study of graphs, a structures used to model pairwise relations between objects. Graph theory includes problems such as the travelling salesman problem and the spectral analysis of graph.

Notebooks
graph_matrix
List matrices describing a finite graph.
graph_coloring
Greedy algorithm for graph coloring.
dijkstra
Find the shortest paths between nodes in a graph.
spectral_graph_theory
Spectral Graph Thoery - PLACEHOLDER (WIP).

Neural Network

Artificial neural networks are composed of artificial neurons organized into layers. Neural networks are employed for regression analysis (function approximation) and classification problems.

Notebooks
ConvNets
face_keypoints
Facial keypoints detection
conv_net
Image classification on CIFAR-10 using CNN
res_net
Image classification on CIFAR-10 using ResNet
Generative Models
ae_fashion_mnist
Autoencoder on Fashion MNIST
variational_autoencoder
Variational autoencoder on MNIST

Stencil Codes

Stencil codes are at the heart of many numerical solvers and physical simulation codes. They are of particular interest in scientific computing research for solving partial differential equations, image processing, cellular automata, etc. The Finite Difference Method (FDM) is closely related to stencil codes.

Notebooks
poisson_solver
Diffusion problem
laplace_inpainting
Laplace inpainting to restore an image
convolution
Image processing with convolution kernels
conway
Cellular automata with Conway's game of life rules

Dimensionality Reduction

Dimensionality reduction is the process of converting data from a high-dimensional space to a low-dimensional space (subspace). A lower dimension representation aids in comprehending meaningful properties (such as latent variables), compressing the data, and removing noise from the original data.

Notebooks
pca_transform
Optimal transformation of a point cloud with PCA
svd_compression
Image compression with Singular Value Decomposition
autoencoder
Autoencoder on Fashion MNIST
eigenfaces
Eigenfaces for face recognition on Olivetti faces dataset

Miscellaneous

Random notebooks about dynamic programming and monte carlo methods

Notebooks
markov_chain
Example of ML pipeline with Snakemake
dynamic_programming
Dynamic programming Examples
monte_carlo_integration
Examples of Monte Carlo integrations
subspace_deformation
Skeletal Subspace Deformation
path_tracing
GitHub
Monte Carlo Path Tracing
markov_chain
Generate authors names from the Collection of Poems from Poetry Foundation
Owner
Vincent Bonnet
Vincent Bonnet
A universal memory dumper using Frida

Fridump Fridump (v0.1) is an open source memory dumping tool, primarily aimed to penetration testers and developers. Fridump is using the Frida framew

551 Jan 07, 2023
Compare GAN code.

Compare GAN This repository offers TensorFlow implementations for many components related to Generative Adversarial Networks: losses (such non-saturat

Google 1.8k Jan 05, 2023
Implementation of our paper "DMT: Dynamic Mutual Training for Semi-Supervised Learning"

DMT: Dynamic Mutual Training for Semi-Supervised Learning This repository contains the code for our paper DMT: Dynamic Mutual Training for Semi-Superv

Zhengyang Feng 120 Dec 30, 2022
POPPY (Physical Optics Propagation in Python) is a Python package that simulates physical optical propagation including diffraction

POPPY: Physical Optics Propagation in Python POPPY (Physical Optics Propagation in Python) is a Python package that simulates physical optical propaga

Space Telescope Science Institute 132 Dec 15, 2022
Autonomous Robots Kalman Filters

Autonomous Robots Kalman Filters The Kalman Filter is an easy topic. However, ma

20 Jul 18, 2022
Official Implementation of "Tracking Grow-Finish Pigs Across Large Pens Using Multiple Cameras"

Multi Camera Pig Tracking Official Implementation of Tracking Grow-Finish Pigs Across Large Pens Using Multiple Cameras CVPR2021 CV4Animals Workshop P

44 Jan 06, 2023
Vehicle speed detection with python

Vehicle-speed-detection In the project simulate the tracker.py first then simulate the SpeedDetector.py. Finally, a new window pops up and the output

3 Dec 15, 2022
YOLOv5🚀 reproduction by Guo Quanhao using PaddlePaddle

YOLOv5-Paddle YOLOv5 🚀 reproduction by Guo Quanhao using PaddlePaddle 支持AutoBatch 支持AutoAnchor 支持GPU Memory 快速开始 使用AIStudio高性能环境快速构建YOLOv5训练(PaddlePa

QuanHao Guo 20 Nov 14, 2022
A fast, dataset-agnostic, deep visual search engine for digital art history

imgs.ai imgs.ai is a fast, dataset-agnostic, deep visual search engine for digital art history based on neural network embeddings. It utilizes modern

Fabian Offert 5 Dec 14, 2022
ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch

ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch

Katherine Crowson 53 Dec 29, 2022
Implementing DeepMind's Fast Reinforcement Learning paper

Fast Reinforcement Learning This is a repo where I implement the algorithms in the paper, Fast reinforcement learning with generalized policy updates.

Marcus Chiam 6 Nov 28, 2022
Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition

Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition How Fast Compare to Other Zero-Shot NAS Proxies on CIFAR-10/100 Pre-trained Model

190 Dec 29, 2022
Keras Realtime Multi-Person Pose Estimation - Keras version of Realtime Multi-Person Pose Estimation project

This repository has become incompatible with the latest and recommended version of Tensorflow 2.0 Instead of refactoring this code painfully, I create

M Faber 769 Dec 08, 2022
This is a model made out of Neural Network specifically a Convolutional Neural Network model

This is a model made out of Neural Network specifically a Convolutional Neural Network model. This was done with a pre-built dataset from the tensorflow and keras packages. There are other alternativ

9 Oct 18, 2022
Running Google MoveNet Multipose Tracking models on OpenVINO.

MoveNet MultiPose Tracking on OpenVINO

60 Nov 17, 2022
Official Implementation of Domain-Aware Universal Style Transfer

Domain Aware Universal Style Transfer Official Pytorch Implementation of 'Domain Aware Universal Style Transfer' (ICCV 2021) Domain Aware Universal St

KibeomHong 80 Dec 30, 2022
An official PyTorch Implementation of Boundary-aware Self-supervised Learning for Video Scene Segmentation (BaSSL)

An official PyTorch Implementation of Boundary-aware Self-supervised Learning for Video Scene Segmentation (BaSSL)

Kakao Brain 72 Dec 28, 2022
Implementation of Squeezenet in pytorch, pretrained models on Cifar 10 data to come

Pytorch Squeeznet Pytorch implementation of Squeezenet model as described in https://arxiv.org/abs/1602.07360 on cifar-10 Data. The definition of Sque

gaurav pathak 86 Oct 28, 2022
Learning Tracking Representations via Dual-Branch Fully Transformer Networks

Learning Tracking Representations via Dual-Branch Fully Transformer Networks DualTFR ⭐ We achieves the runner-ups for both VOT2021ST (short-term) and

phiphi 19 May 04, 2022
Omnidirectional camera calibration in python

Omnidirectional Camera Calibration Key features pure python initial solution based on A Toolbox for Easily Calibrating Omnidirectional Cameras (Davide

Thomas Pönitz 12 Nov 22, 2022