janvr97

janvr97's Stars

• Valdecy/pyCombinatorial

  A library to solve the TSP (Travelling Salesman Problem) using Exact Algorithms, Heuristics and Metaheuristics : 2-opt; 2.5-opt; 3-opt; 4-opt; 5-opt; 2-opt Stochastic; 2.5-opt Stochastic; 3-opt Stochastic; 4-opt Stochastic; 5-opt Stochastic; Ant Colony Optimization; Bellman-Held-Karp Exact Algorithm; Branch & Bound; BRKGA (Biased Random Key Genetic Algorithm); Brute Force; Cheapest Insertion; Christofides Algorithm; Clarke & Wright (Savings Heuristic); Concave Hull Algorithm; Convex Hull Algorithm; Elastic Net; Extremal Optimization; Farthest Insertion; Genetic Algorithm; GRASP (Greedy Randomized Adaptive Search Procedure); Greedy Karp-Steele Patching; Guided Search; Hopfield Network; Iterated Search; Karp-Steele Patching; Multifragment Heuristic; Nearest Insertion; Nearest Neighbour; Random Insertion; Random Tour; Scatter Search; Simulated Annealing; SOM (Self Organizing Maps); Space Filling Curve (Hilbert); Space Filling Curve (Morton); Space Filling Curve (Sierpinski); Stochastic Hill Climbing; Sweep; Tabu Search; Truncated Branch & Bound; Twice-Around the Tree Algorithm (Double Tree Algorithm); Variable Neighborhood Search.

  Language:Python10515

• joeeliang/DoublePendulum

  Lyapunov Exponents in the Double Pendulum

  Language:Python483

• raunak/Travelling-Salesman-Problem

  Language:Python23

• gjbex/EssentialLaTeX

  Narrow scope LaTeX introduction, intended for contributors to technical manuals or tutorials.

  Language:TeX2

• gjbex/MigrationBelgium

  Streamlit application to visualize migration background in Belgium

  Language:Python1

• gjbex/vsc_user_docs

  VSC user training material and documentation

  Language:TeX1

• gjbex/Materializer

  Python script to make a pictures "materialize" out of a stream of bits in the terminal

  Language:Jupyter Notebook1

• gjbex/MapMaker

  Map Maker lets you create chloropleth maps of Belgium using data in an Excel or CSV file. The webapplication uses steramlit.

  Language:Python1

• gjbex/training-material

  A collection of code examples as well as presentations for training purposes

  Language:Jupyter Notebook12152

• gjbex/ChatGPT-for-HPC

  This repository contains material for a training on using tools such as ChatGPT and Github Copilot in the context of software engineering and High-Performance Computing (HPC).

  5

• gjbex/Python-on-GPUs

  Repository for the training on using GPUs from Python.

  Language:Jupyter Notebook83

• gjbex/Version-control-with-git

  Repository for participants of the "Version control with git" training

  Language:Jupyter Notebook76

• gjbex/Machine-learning-with-Python

  Repository for participants of the "Machine learning with Python" training

  Language:Jupyter Notebook1424

• gjbex/Scientific-Python

  Repository for participants of the "Scientific Python" training

  Language:Jupyter Notebook1912

• gjbex/Parallel-programming

  Material for a training on parallel programming with MPI, OpenMP and TBB.

  Language:Jupyter Notebook71

• gjbex/Python-for-programmers

  Repository for participants of the "Python for programmers" training

  Language:Jupyter Notebook21

• gjbex/Cheatsheets

  Collection of cheat sheets

  32

• gjbex/Python-for-systems-programming

  Repository for participants of the "Python for systems programming" training

  Language:Jupyter Notebook4011

• gjbex/GPU-programming

  Material for a training on portable GPU programming

  Language:C++2

• hpcleuven/Slurm-lunchbox

  Slides and example scripts for the lunchbox session on the Slurm scheduler.

  11

• hpcleuven/Linux-scripting

  Slides, exercises and extra files for the Linux scripting course at KU Leuven

  64

• gjbex/Python-for-data-science

  Repository for participants of the "Python for data science" training

  Language:Jupyter Notebook1719

• ted-piotrowski/shademap-examples

  Use cases for ShadeMap API

  5

• mbobra/SHARPs

  The SHARP data includes images of active regions, together with metadata keywords that describe their characteristics, taken by the NASA Solar Dynamics Observatory

  Language:Jupyter Notebook3925

• hpcleuven/Linux-intro

  Slides, exercises and extra files for the Linux intro course at KU Leuven

  21

• hpcleuven/HPC-intro

  Slides, exercises and extra files for the HPC intro course at KU Leuven

  235

• lucabergamini/VAEGAN-PYTORCH

  VAEGAN from "Autoencoding beyond pixels using a learned similarity metric" implemented in Pytorch. Clean, clear and with comments.

  Language:Python18434

• TiboVermeersch/Optimizing-a-Disentangled-Variational-AutoEncoder-to-generate-artificial-active-regions

  Language:Python1

• jaanli/variational-autoencoder

  Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)

  Language:Python1.1k256

• gullyn/astar

  Visualization of the A* search algorithm

  Language:HTML222