Python Rosenbrock-function-optimization Resources

Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend This project acts as both a tuto

FunctionPlotter GUI Python program that plots functions that are entered by the user. The program takes minimum and maximum value for x and plot it as

stream-write-ods Python function to construct an ODS (OpenDocument Spreadsheet) on the fly - without having to store the entire file in memory or disk

Training Script for Reuse-VOS This code implementation of CVPR 2021 paper : Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Vi

Img-process-manual - Opencv Library basic graphic processing algorithm coding reproduction based on Numpy and Matplotlib library

Must-typing Force you (or your user) annotate function type hints. Notice: It's more like a joke, use it carefully. If you call must_typing in your mo

Weather Underground → Influx DB 🌤 Serverless function for replicating Weather U

Python function to construct a ZIP archive with on the fly - without having to store the entire ZIP in memory or disk

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This is my favourite function - the Rastrigin function. What sparked my curiosity and interest in the function was its complexity in terms of many local optimum points, which makes it particularly interesting and useful for testing any optimisation algorithms.

pycsminwel This is a locol minimization algorithm. Uses a quasi-Newton method with BFGS update of the estimated inverse hessian. It is robust against

MADGRAD Optimization Method A Momentumized, Adaptive, Dual Averaged Gradient Method for Stochastic Optimization pip install madgrad Try it out! A best

fastapi-cache Introduction fastapi-cache is a tool to cache fastapi response and function result, with backends support redis, memcache, and dynamodb.

FastAPI Zeit Now Deploy a FastAPI app as a Zeit Serverless Function. This repo deploys the FastAPI SQL Databases Tutorial to demonstrate how a FastAPI

Function-Plotter Build With : Python PyQt5 unittest matplotlib Getting Started This is an list of needed instructions to set up your project locally,

Logo by Zhuoning Yuan LibAUC: A Machine Learning Library for AUC Optimization Website | Updates | Installation | Tutorial | Research | Github LibAUC a

Cookiecutter Google Function Cookiecutter template for a Google Function. Powered by Poetry, and GitHub actions. Quickstart Install the latest Cookiec

Flyable - A python compiler for highly performant code Flyable is a Python compiler that generates efficient native code. It uses different techniques

pypemdas Pure python PEMDAS expression solver without using built-in eval function. Supports nested parenthesis. Supported operators: + - * / ^ Exampl

Python HPC Optimizaciones incrementales de N-Body (all-pairs) con el fin de evaluar y comparar las prestaciones de los traductores de Python en el ámb

Curriculum Dropout Dropout is a very effective way of regularizing neural networks. Stochastically "dropping out" units with a certain probability dis

Fiber implements an proof-of-concept Python decorator that rewrites a function so that it can be paused and resumed (by moving stack variables to a heap frame and adding if statements to simulate jumps/gotos to specific lines of code).

O S L O Open Source framework for Large-scale transformer Optimization What's New: December 21, 2021 Released OSLO 1.0. What is OSLO about? OSLO is a

PPOPT Python Parametric OPtimization Toolbox (PPOPT) is a software platform for solving and manipulating multiparametric programs in Python. This pack

CFMM Optimal Routing This repository contains the code needed to generate the figures used in the paper Optimal Routing for Constant Function Market M

pybnb A parallel branch-and-bound engine for Python. This software is copyright (c) by Gabriel A. Hackebeil (gabe.hacke

STORM Stochastic Tensor Optimization for Robot Motion - A GPU Robot Motion Toolkit [Install Instructions] [Paper] [Website] This package contains code

AdversarialTexture Adversarial Texture Optimization from RGB-D Scans (CVPR 2020). Scanning Data Download Please refer to data directory for details. B

Sklearn-genetic-opt scikit-learn models hyperparameters tuning and feature selection, using evolutionary algorithms. This is meant to be an alternativ

The source code is temporariy removed, as we are solving potential copyright and license issues with GRANSO (http://www.timmitchell.com/software/GRANS

Pretrained Language Model This repository provides the latest pretrained language models and its related optimization techniques developed by Huawei N

COSCO Framework COSCO is an AI based coupled-simulation and container orchestration framework for integrated Edge, Fog and Cloud Computing Environment

flake8-annotations flake8-annotations is a plugin for Flake8 that detects the absence of PEP 3107-style function annotations and PEP 484-style type co

Simulation and Parameter Estimation in Geophysics - A python package for simulation and gradient based parameter estimation in the context of geophysical applications.

Soft-Exponential-Activation-Function: Implementation of parameterized soft-exponential activation function. In this implementation, the parameters are

PyGAD: Genetic Algorithm in Python PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine lear

NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.

Monte Carlo python simulation Install linux dependencies sudo apt update sudo apt install build-essential \ software-properties-commo

Python flexible slugify function

KIDA: Knowledge Inheritance in Data Aggregation This project releases our 1st place solution on NeurIPS2021 ML4CO Dual Task. Slide and model weights a

[NeurIPS 2021] Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects YouTube | arXiv Prerequisites Kaolin is available here:

geneticml This package contains a simple and lightweight genetic algorithm for optimization of any machine learning model. Installation Use pip to ins

Pretrained Cost Model for Distributed Constraint Optimization Problems Requirements PyTorch 1.9.0 PyTorch Geometric 1.7.1 Directory structure baseline

Flower plot A Python 3.9+ function that makes flower plots. Installation This package requires at least Python 3.9. pip install

geneticml This package contains a simple and lightweight genetic algorithm for optimization of any machine learning model. Installation Use pip to ins

A function decorator for enforcing function signatures

ASCII Graph Plotter Plots the graph of a function with ASCII characters. See the change log here. Developed by InformaticFreak (c) 2021 How to use py

Alternatives to Deep Neural Networks for Function Approximations in Finance Code companion repo Overview This is a repository of Python code to go wit

FedTorch is a generic repository for benchmarking different federated and distributed learning algorithms using PyTorch Distributed API.

CTO (Call Tree Overviewer) CTO (Call Tree Overviewer) is an IDA plugin for creating a simple and efficiant function call tree graph. It can also summa

Custom Object Tracking Introduction This repo provides function call to track multi-objects in videos with a given trained object detection model and

FuseDream This repo contains code for our paper (paper link): FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimizat

pytest-is-running pytest plugin providing a function to check if pytest is running. Installation Install with: python -m pip install pytest-is-running

Bayesian Optimization over Permutation Spaces This repository contains the source code and the resources related to the paper "Bayesian Optimization o

PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural ne

slientruss3d : Python for stable truss analysis tool Desciption slientruss3d is a python package which can solve the resistances, internal forces and

Theseus A library for differentiable nonlinear optimization built on PyTorch to support constructing various problems in robotics and vision as end-to

This repository contains the similarity metrics designed and evaluated in the paper, and instructions and code to re-run the experiments. Implementation in the deep-learning framework PyTorch

Reviatalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation This is the implementation of the approach describ

exhaust A Python library to exhaustively enumerate a combinatorial space represented by a function. The API is modelled after Python's random module a

Grow Function: A 3D Stacked Bifurcating Double Deep Cellular Automata which differentiates using a Genetic Algorithm... TLDR;High Def Trees that you can mint as NFTs on Solana

Attractors A small module that provides functions and classes for very efficient simulation and rendering of iterated function systems; dynamical syst

probability-density-function General info An application that calculates the probability density and cumulative distribution of a normal distribution

Milano (This is a research project, not an official NVIDIA product.) Documentation https://nvidia.github.io/Milano Milano (Machine learning autotuner

DeepSpeed+Megatron trained the world's most powerful language model: MT-530B DeepSpeed is hiring, come join us! DeepSpeed is a deep learning optimizat

Pretrained Language Model This repository provides the latest pretrained language models and its related optimization techniques developed by Huawei N

iftopt An Implicit Function Theorem (IFT) optimizer for bi-level optimizations. Requirements Python 3.7+ PyTorch 1.x Installation $ pip install git+ht

Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-Learning This is the official repository of "Camera Distortion-

sNewton4PDEOpt The Python module implements a semismooth Newton method for solving finite-element discretizations of the strongly convex, linear ellip

Optimized Einsum Optimized Einsum: A tensor contraction order optimizer Optimized einsum can significantly reduce the overall execution time of einsum

Algorithmic trading backtest and optimization examples using order book imbalances. (bitcoin, cryptocurrency, bitmex)

8QueensGenetic A Python project for optimizing the 8 Queens Puzzle using the Genetic Algorithm implemented in PyGAD. The project uses the Kivy cross-p

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 NCVX: A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning. Please check https://ncvx.org for detailed instruction

SMU_pytorch A Pytorch Implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE arXiv https://arxiv.org/ab

route-planner Functions api_processing Use this function to get list of routes for particular journey. Function has three parameters: Origin Destinati

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

Syne Tune This package provides state-of-the-art distributed hyperparameter optimizers (HPO) where trials can be evaluated with several backend option

DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation This repository is the implementation of DynaTune paper. This folder

pytest-idempotent Pytest plugin for testing the idempotency of a function. Usage pip install pytest-idempotent Documentation Suppose we had the follo

g2o - General Graph Optimization Linux: Windows: g2o is an open-source C++ framework for optimizing graph-based nonlinear error functions. g2o has bee

PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization News: [2020/05/04] Added EGL rendering option for training data g

Upgrade your print statements Loggers are like print() statements except they also include loads of other metadata: timestamp msg (same as print!) arg

Riskfolio-Lib Quantitative Strategic Asset Allocation, Easy for Everyone. Description Riskfolio-Lib is a library for making quantitative strategic ass

MeTAL - Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning (ICCV2021 Oral) Sungyong Baik, Janghoon Choi, Heewon Kim, Dohee Cho, Jaes

Please consider citing the manuscript if you use apricot in your academic work! You can find more thorough documentation here. apricot implements subm

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. Hyperactive: is very easy to lear

Python Library stats This is a small library that allows you to query some useful statistics for Python code-bases. We currently report library import

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.

DA2Lite (Deep Architecture to Lite) is a toolkit to compress and accelerate deep network models. ⭐ Star us on GitHub — it helps!! Frameworks & Librari

A python package to manage the stored receiver-side Strain Green's Tensor (SGT) database of 3D background models and able to generate Green's function and synthetic waveform

early-ML Presentation General Machine Learning tutorials A Python step-by-step primer for Machine Learning and Optimization This github repository gat

Universal Activation Function Tensorflow and Pytorch source code for the paper Yuen, Brosnan, Minh Tu Hoang, Xiaodai Dong, and Tao Lu. "Universal acti

By Investors, For Investors. Want to read this in Chinese? Click here Empyrial is a Python-based open-source quantitative investment library dedicated

What is DeepHyper? DeepHyper is a software package that uses learning, optimization, and parallel computing to automate the design and development of

Simple but powerful Automated Machine Learning library for tabular data. It uses efficient in-memory SAP HANA algorithms to automate routine Data Scie

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

For specific function. For my own convenience. Remind owner to share data to another DITO user.

Racing Line Optimization with PSO This repository contains a racing line optimization algorithm in python that uses Particle Swarm Optimization. Requi