512 Repositories
Python amortized-optimization-tutorial Libraries
Algorithm for Cutting Stock Problem using Google OR-Tools. Link to the tool:
Cutting Stock Problem Cutting Stock Problem (CSP) deals with planning the cutting of items (rods / sheets) from given stock items (which are usually o
NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.
NCVX NCVX: A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning. Please check https://ncvx.org for detailed instruction
Ant Colony Optimization for Traveling Salesman Problem
tsp-aco Ant Colony Optimization for Traveling Salesman Problem Dependencies Python 3.8 tqdm numpy matplotlib To run the solver run main.py from the p
Large scale and asynchronous Hyperparameter Optimization at your fingertip.
Syne Tune This package provides state-of-the-art distributed hyperparameter optimizers (HPO) where trials can be evaluated with several backend option
A simple and extensible library to create Bayesian Neural Network layers on PyTorch.
Blitz - Bayesian Layers in Torch Zoo BLiTZ is a simple and extensible library to create Bayesian Neural Network Layers (based on whats proposed in Wei
DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation
DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation This repository is the implementation of DynaTune paper. This folder
The tutorial is a collection of many other resources and my own notes
Why we need CTC? --- looking back on history 1.1. About CRNN 1.2. from Cross Entropy Loss to CTC Loss Details about CTC 2.1. intuition: forward algor
g2o: A General Framework for Graph Optimization
g2o - General Graph Optimization Linux: Windows: g2o is an open-source C++ framework for optimizing graph-based nonlinear error functions. g2o has bee
Yaml - Loggers are like print() statements
Upgrade your print statements Loggers are like print() statements except they also include loads of other metadata: timestamp msg (same as print!) arg
Portfolio Optimization and Quantitative Strategic Asset Allocation in Python
Riskfolio-Lib Quantitative Strategic Asset Allocation, Easy for Everyone. Description Riskfolio-Lib is a library for making quantitative strategic ass
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
Yolo v4, v3 and v2 for Windows and Linux (neural networks for object detection) Paper YOLO v4: https://arxiv.org/abs/2004.10934 Paper Scaled YOLO v4:
An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.
Welcome to AdaptNLP A high level framework and library for running, training, and deploying state-of-the-art Natural Language Processing (NLP) models
Tutorial in Python targeted at Epidemiologists. Will discuss the basics of analysis in Python 3
Python-for-Epidemiologists This repository is an introduction to epidemiology analyses in Python. Additionally, the tutorials for my library zEpid are
apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly.
Please consider citing the manuscript if you use apricot in your academic work! You can find more thorough documentation here. apricot implements subm
Universal Probability Distributions with Optimal Transport and Convex Optimization
Sylvester normalizing flows for variational inference Pytorch implementation of Sylvester normalizing flows, based on our paper: Sylvester normalizing
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear
ROS2 Docker tutorial with VSCode
ROS2-Docker-tutorial I made this repository using athackst/vscode_ros2_workspace templete with foxy-nvidia branch. You could see more information abov
Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation. Intel iHD GPU (iGPU) support. NVIDIA GPU (dGPU) support.
mtomo Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation.
A tutorial on training a DarkNet YOLOv4 model for the CrowdHuman dataset
YOLOv4 CrowdHuman Tutorial This is a tutorial demonstrating how to train a YOLOv4 people detector using Darknet and the CrowdHuman dataset. Table of c
DA2Lite is an automated model compression toolkit for PyTorch.
DA2Lite (Deep Architecture to Lite) is a toolkit to compress and accelerate deep network models. ⭐ Star us on GitHub — it helps!! Frameworks & Librari
Single cell current best practices tutorial case study for the paper:Luecken and Theis, "Current best practices in single-cell RNA-seq analysis: a tutorial"
Scripts for "Current best-practices in single-cell RNA-seq: a tutorial" This repository is complementary to the publication: M.D. Luecken, F.J. Theis,
A Python step-by-step primer for Machine Learning and Optimization
early-ML Presentation General Machine Learning tutorials A Python step-by-step primer for Machine Learning and Optimization This github repository gat
nlp-tutorial is a tutorial for who is studying NLP(Natural Language Processing) using Pytorch
nlp-tutorial is a tutorial for who is studying NLP(Natural Language Processing) using Pytorch. Most of the models in NLP were implemented with less than 100 lines of code.(except comments or blank lines)
TensorFlow Tutorials with YouTube Videos
TensorFlow Tutorials Original repository on GitHub Original author is Magnus Erik Hvass Pedersen Introduction These tutorials are intended for beginne
Empyrial is a Python-based open-source quantitative investment library dedicated to financial institutions and retail investors
By Investors, For Investors. Want to read this in Chinese? Click here Empyrial is a Python-based open-source quantitative investment library dedicated
DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks
What is DeepHyper? DeepHyper is a software package that uses learning, optimization, and parallel computing to automate the design and development of
Python Automated Machine Learning library for tabular data.
Simple but powerful Automated Machine Learning library for tabular data. It uses efficient in-memory SAP HANA algorithms to automate routine Data Scie
Introducing neural networks to predict stock prices
IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o
Dynamic Programming-Join Optimization Algorithm
DP-JOA Join optimization is the process of optimizing the joining, or combining, of two or more tables in a database. Here is a simple join optimizati
Racing line optimization algorithm in python that uses Particle Swarm Optimization.
Racing Line Optimization with PSO This repository contains a racing line optimization algorithm in python that uses Particle Swarm Optimization. Requi
Visualization of numerical optimization algorithms
Visualization of numerical optimization algorithms
Simulation code and tutorial for BBHnet training data
Simulation Dataset for BBHnet NOTE: OLD README, UPDATE IN PROGRESS We generate simulation dataset to train BBHnet, our deep learning framework for det
An example project which contains the Unity components necessary to complete Navigation2's SLAM tutorial with a Turtlebot3, using a custom Unity environment in place of Gazebo.
Navigation 2 SLAM Example This example provides a Unity Project and a colcon workspace that, when used together, allows a user to substitute Unity as
This repository contains Prior-RObust Bayesian Optimization (PROBO) as introduced in our paper "Accounting for Gaussian Process Imprecision in Bayesian Optimization"
Prior-RObust Bayesian Optimization (PROBO) Introduction, TOC This repository contains Prior-RObust Bayesian Optimization (PROBO) as introduced in our
This is the reference implementation for "Coresets via Bilevel Optimization for Continual Learning and Streaming"
Coresets via Bilevel Optimization This is the reference implementation for "Coresets via Bilevel Optimization for Continual Learning and Streaming" ht
Time Series Cross-Validation -- an extension for scikit-learn
TSCV: Time Series Cross-Validation This repository is a scikit-learn extension for time series cross-validation. It introduces gaps between the traini
Statistical and Algorithmic Investing Strategies for Everyone
Eiten - Algorithmic Investing Strategies for Everyone Eiten is an open source toolkit by Tradytics that implements various statistical and algorithmic
Gaussian Process Optimization using GPy
End of maintenance for GPyOpt Dear GPyOpt community! We would like to acknowledge the obvious. The core team of GPyOpt has moved on, and over the past
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture
CVXPY is a Python-embedded modeling language for convex optimization problems.
CVXPY The CVXPY documentation is at cvxpy.org. We are building a CVXPY community on Discord. Join the conversation! For issues and long-form discussio
Nevergrad - A gradient-free optimization platform
Nevergrad - A gradient-free optimization platform nevergrad is a Python 3.6+ library. It can be installed with: pip install nevergrad More installati
A Python module for parallel optimization of expensive black-box functions
blackbox: A Python module for parallel optimization of expensive black-box functions What is this? A minimalistic and easy-to-use Python module that e
Neural Architecture Search Powered by Swarm Intelligence 🐜
Neural Architecture Search Powered by Swarm Intelligence 🐜 DeepSwarm DeepSwarm is an open-source library which uses Ant Colony Optimization to tackle
A hyperparameter optimization framework
Optuna: A hyperparameter optimization framework Website | Docs | Install Guide | Tutorial Optuna is an automatic hyperparameter optimization software
Black box hyperparameter optimization made easy.
BBopt BBopt aims to provide the easiest hyperparameter optimization you'll ever do. Think of BBopt like Keras (back when Theano was still a thing) for
A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
Alpha Zero General (any game, any framework!) A simplified, highly flexible, commented and (hopefully) easy to understand implementation of self-play
Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras
Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras This tutorial shows how to use Keras library to build deep ne
PyTorch implementation of Federated Learning with Non-IID Data, and federated learning algorithms, including FedAvg, FedProx.
Federated Learning with Non-IID Data This is an implementation of the following paper: Yue Zhao, Meng Li, Liangzhen Lai, Naveen Suda, Damon Civin, Vik
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees This repository is the official implementation of the empirica
ProsePainter combines direct digital painting with real-time guided machine-learning based image optimization.
ProsePainter Create images by painting with words. ProsePainter combines direct digital painting with real-time guided machine-learning based image op
Music Classification: Beyond Supervised Learning, Towards Real-world Applications
Music Classification: Beyond Supervised Learning, Towards Real-world Applications
Hypersearch weight debugging and losses tutorial
tutorial Activate tensorboard option Running TensorBoard remotely When working on a remote server, you can use SSH tunneling to forward the port of th
CINECA molecular dynamics tutorial set
High Performance Molecular Dynamics Logging into CINECA's computer systems To logon to the M100 system use the following command from an SSH client ss
Multi-objective constrained optimization for energy applications via tree ensembles
Multi-objective constrained optimization for energy applications via tree ensembles
BlueFog Tutorials
BlueFog Tutorials Welcome to the BlueFog tutorials! In this repository, we've put together a collection of awesome Jupyter notebooks. These notebooks
Explaining Hyperparameter Optimization via PDPs
Explaining Hyperparameter Optimization via PDPs This repository gives access to an implementation of the methods presented in the paper submission “Ex
Safe Policy Optimization with Local Features
Safe Policy Optimization with Local Feature (SPO-LF) This is the source-code for implementing the algorithms in the paper "Safe Policy Optimization wi
Open-Source Tools & Data for Music Source Separation: A Pragmatic Guide for the MIR Practitioner
Open-Source Tools & Data for Music Source Separation: A Pragmatic Guide for the MIR Practitioner
Safe Policy Optimization with Local Features
Safe Policy Optimization with Local Feature (SPO-LF) This is the source-code for implementing the algorithms in the paper "Safe Policy Optimization wi
Start-to-finish tutorial for interactive music co-creation in PyTorch and Tensorflow.js
Start-to-finish tutorial for interactive music co-creation in PyTorch and Tensorflow.js
Neural Scene Flow Prior (NeurIPS 2021 spotlight)
Neural Scene Flow Prior Xueqian Li, Jhony Kaesemodel Pontes, Simon Lucey Will appear on Thirty-fifth Conference on Neural Information Processing Syste
The materials used in the SaxonJS tutorial presented at Declarative Amsterdam, 2021
SaxonJS-Tutorial-2021, version 1.0.4 Last updated on 4 November, 2021. Table of contents Background Prerequisites Starting a web server Running a Java
Tools for Optuna, MLflow and the integration of both.
HPOflow - Sphinx DOC Tools for Optuna, MLflow and the integration of both. Detailed documentation with examples can be found here: Sphinx DOC Table of
Codes for CVPR2021 paper "PWCLO-Net: Deep LiDAR Odometry in 3D Point Clouds Using Hierarchical Embedding Mask Optimization"
PWCLO-Net: Deep LiDAR Odometry in 3D Point Clouds Using Hierarchical Embedding Mask Optimization (CVPR 2021) This is the official implementation of PW
2021-AIAC-QQ-Browser-Hyperparameter-Optimization-Rank6
2021-AIAC-QQ-Browser-Hyperparameter-Optimization-Rank6
A Lightweight Hyperparameter Optimization Tool 🚀
Lightweight Hyperparameter Optimization 🚀 The mle-hyperopt package provides a simple and intuitive API for hyperparameter optimization of your Machin
A comprehensive tutorial for plotting focal mechanism
Focal_Mechanisms_Demo A comprehensive tutorial for plotting focal mechanism "beach-balls" using the PyGMT package for Python. (Resulting map of this d
In this tutorial, raster models of soil depth and soil water holding capacity for the United States will be sampled at random geographic coordinates within the state of Colorado.
Raster_Sampling_Demo (Resulting graph of this demo) Background Sampling values of a raster at specific geographic coordinates can be done with a numbe
Source code for deep symbolic optimization.
Update July 10, 2021: This repository now supports an additional symbolic optimization task: learning symbolic policies for reinforcement learning. Th
Generalized Proximal Policy Optimization with Sample Reuse (GePPO)
Generalized Proximal Policy Optimization with Sample Reuse This repository is the official implementation of the reinforcement learning algorithm Gene
Generalized and Efficient Blackbox Optimization System.
OpenBox Doc | OpenBox中文文档 OpenBox: Generalized and Efficient Blackbox Optimization System OpenBox is an efficient and generalized blackbox optimizatio
Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces
This repository contains source code for the paper Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces a
Bayesian Optimization Library for Medical Image Segmentation.
bayesmedaug: Bayesian Optimization Library for Medical Image Segmentation. bayesmedaug optimizes your data augmentation hyperparameters for medical im
Code for "Adversarial Attack Generation Empowered by Min-Max Optimization", NeurIPS 2021
Min-Max Adversarial Attacks [Paper] [arXiv] [Video] [Slide] Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang, Tianyun Zha
This is a tutorial on how to make a Discord Bot using the discord.py library
HowToMakeADiscordBot This Github repository is here to help you code a Discord Bot using the discord.py library! 1 - Setup: Download the code inside t
This project is based on our SIGGRAPH 2021 paper, ROSEFusion: Random Optimization for Online DenSE Reconstruction under Fast Camera Motion .
ROSEFusion 🌹 This project is based on our SIGGRAPH 2021 paper, ROSEFusion: Random Optimization for Online DenSE Reconstruction under Fast Camera Moti
Implementation of our NeurIPS 2021 paper "A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs".
PPO-BiHyb This is the official implementation of our NeurIPS 2021 paper "A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Grap
A simple tutorial to get you started with Discord and it's Python API
Hello there Feel free to fork and star, open issues if there are typos or you have a doubt. I decided to make this post because as a newbie I never fo
Tutorial for STARKs with supporting code in python
stark-anatomy STARK tutorial with supporting code in python Outline: introduction overview of STARKs basic tools -- algebra and polynomials FRI low de
🔥 Real-time Super Resolution enhancement (4x) with content loss and relativistic adversarial optimization 🔥
🔥 Real-time Super Resolution enhancement (4x) with content loss and relativistic adversarial optimization 🔥
[NeurIPS 2021] Official implementation of paper "Learning to Simulate Self-driven Particles System with Coordinated Policy Optimization".
Code for Coordinated Policy Optimization Webpage | Code | Paper | Talk (English) | Talk (Chinese) Hi there! This is the source code of the paper “Lear
This repo is the official implementation of "L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization".
L2ight is a closed-loop ONN on-chip learning framework to enable scalable ONN mapping and efficient in-situ learning. L2ight adopts a three-stage learning flow that first calibrates the complicated photonic circuit states under challenging physical constraints, then performs photonic core mapping via combined analytical solving and zeroth-order optimization.
Repository for learning Python (Python Tutorial)
Repository for learning Python (Python Tutorial) Languages and Tools 🧰 Overview 📑 Repository for learning Python (Python Tutorial) Languages and Too
A tutorial for people to run synthetic data replica's from source healthcare datasets
Synthetic-Data-Replica-for-Healthcare Description What is this? A tailored hands-on tutorial showing how to use Python to create synthetic data replic
With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function
With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function. At the moment, only TensorFlow sequential models are supported. Interfaces to either the Pyomo or Gurobi modeling environments are offered.
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees This repository is the official implementation of the empirica
Dynamica causal Bayesian optimisation
Dynamic Causal Bayesian Optimization This is a Python implementation of Dynamic Causal Bayesian Optimization as presented at NeurIPS 2021. Abstract Th
RoMA: Robust Model Adaptation for Offline Model-based Optimization
RoMA: Robust Model Adaptation for Offline Model-based Optimization Implementation of RoMA: Robust Model Adaptation for Offline Model-based Optimizatio
An implementation of the proximal policy optimization algorithm
PPO Pytorch C++ This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment t
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
Trajectory optimization package for Mini-Pupper robot
Trajectory optimization package for Mini-Pupper robot Purpose of this repository is to provide low-torque and low-impact trajectory for Mini-Pupper qu
A Lightweight Hyperparameter Optimization Tool 🚀
The mle-hyperopt package provides a simple and intuitive API for hyperparameter optimization of your Machine Learning Experiment (MLE) pipeline.
Tools for investing in Python
InvestOps Original repository on GitHub Original author is Magnus Erik Hvass Pedersen Introduction This is a Python package with simple and effective
OpenNeoMC:an Open-source Tool for Particle Transport Optimization that Combining OpenMC with NEORL
OpenNeoMC:an Open-source Tool for Particle Transport Optimization that Combining OpenMC with NEORL OpenMC is a community-developed Monte Carlo neutron
Django Girls Tutorial Workshop
Django Girls Tutorial Workshop A log of activities during the workshop. this is an H2 git remote add origin https://github.com/ahuimanu/django_girls_t
A lightweight Python-based 3D network multi-agent simulator. Uses a cell-based congestion model. Calculates risk, loudness and battery capacities of the agents. Suitable for 3D network optimization tasks.
AMAZ3DSim AMAZ3DSim is a lightweight python-based 3D network multi-agent simulator. It uses a cell-based congestion model. It calculates risk, battery
This tutorial will guide you through the process of self-hosting Polygon
Hosting guide This tutorial will guide you through the process of self-hosting Polygon Before starting Make sure you have the following tools installe
NAS-HPO-Bench-II is the first benchmark dataset for joint optimization of CNN and training HPs.
NAS-HPO-Bench-II API Overview NAS-HPO-Bench-II is the first benchmark dataset for joint optimization of CNN and training HPs. It helps a fair and low-
Code and datasets for the paper "KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction"
KnowPrompt Code and datasets for our paper "KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction" Requireme
A bare-bones Python library for quality diversity optimization.
pyribs Website Source PyPI Conda CI/CD Docs Docs Status Twitter pyribs.org GitHub docs.pyribs.org A bare-bones Python library for quality diversity op