Python Auc-optimization Resources

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

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

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

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

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

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

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

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

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

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

Prior-RObust Bayesian Optimization (PROBO) Introduction, TOC This repository contains Prior-RObust Bayesian Optimization (PROBO) as introduced in our

Coresets via Bilevel Optimization This is the reference implementation for "Coresets via Bilevel Optimization for Continual Learning and Streaming" ht

TSCV: Time Series Cross-Validation This repository is a scikit-learn extension for time series cross-validation. It introduces gaps between the traini

Eiten - Algorithmic Investing Strategies for Everyone Eiten is an open source toolkit by Tradytics that implements various statistical and algorithmic

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

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 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 is a Python 3.6+ library. It can be installed with: pip install nevergrad More installati

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 🐜 DeepSwarm DeepSwarm is an open-source library which uses Ant Colony Optimization to tackle

Optuna: A hyperparameter optimization framework Website | Docs | Install Guide | Tutorial Optuna is an automatic hyperparameter optimization software

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

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 This repository is the official implementation of the empirica

ProsePainter Create images by painting with words. ProsePainter combines direct digital painting with real-time guided machine-learning based image op

Multi-objective constrained optimization for energy applications via tree ensembles

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 Feature (SPO-LF) This is the source-code for implementing the algorithms in the paper "Safe Policy Optimization wi

Safe Policy Optimization with Local Feature (SPO-LF) This is the source-code for implementing the algorithms in the paper "Safe Policy Optimization wi

Neural Scene Flow Prior Xueqian Li, Jhony Kaesemodel Pontes, Simon Lucey Will appear on Thirty-fifth Conference on Neural Information Processing Syste

HPOflow - Sphinx DOC Tools for Optuna, MLflow and the integration of both. Detailed documentation with examples can be found here: Sphinx DOC Table of

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

Lightweight Hyperparameter Optimization 🚀 The mle-hyperopt package provides a simple and intuitive API for hyperparameter optimization of your Machin

fastauc Two fast AUC calculation implementations for python: python-based is approximately 5X faster than the default sklearn.metrics.roc_auc_score()

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 This repository is the official implementation of the reinforcement learning algorithm Gene

OpenBox Doc | OpenBox中文文档 OpenBox: Generalized and Efficient Blackbox Optimization System OpenBox is an efficient and generalized blackbox optimizatio

This repository contains source code for the paper Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces a

bayesmedaug: Bayesian Optimization Library for Medical Image Segmentation. bayesmedaug optimizes your data augmentation hyperparameters for medical im

Min-Max Adversarial Attacks [Paper] [arXiv] [Video] [Slide] Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang, Tianyun Zha

ROSEFusion 🌹 This project is based on our SIGGRAPH 2021 paper, ROSEFusion: Random Optimization for Online DenSE Reconstruction under Fast Camera Moti

PPO-BiHyb This is the official implementation of our NeurIPS 2021 paper "A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Grap

🔥 Real-time Super Resolution enhancement (4x) with content loss and relativistic adversarial optimization 🔥

Code for Coordinated Policy Optimization Webpage | Code | Paper | Talk (English) | Talk (Chinese) Hi there! This is the source code of the paper “Lear

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.

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 This repository is the official implementation of the empirica

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 Implementation of RoMA: Robust Model Adaptation for Offline Model-based Optimizatio

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).

Trajectory optimization package for Mini-Pupper robot Purpose of this repository is to provide low-torque and low-impact trajectory for Mini-Pupper qu

The mle-hyperopt package provides a simple and intuitive API for hyperparameter optimization of your Machine Learning Experiment (MLE) pipeline.

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 OpenMC is a community-developed Monte Carlo neutron

AMAZ3DSim AMAZ3DSim is a lightweight python-based 3D network multi-agent simulator. It uses a cell-based congestion model. It calculates risk, battery

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-

KnowPrompt Code and datasets for our paper "KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction" Requireme

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

What is Retentioneering? Retentioneering is a Python framework and library to assist product analysts and marketing analysts as it makes it easier to

offline-MBPO This repository contains the code of a version of model-based RL algorithm MBPO, which is modified to perform in offline RL settings Pape

V-MPO Simple code to demonstrate Deep Reinforcement Learning by using an on-policy adaptation of Maximum a Posteriori Policy Optimization (MPO) in Pyt

TensorFlow RiemOpt A library for manifold-constrained optimization in TensorFlow. Installation To install the latest development version from GitHub:

Image-Optimizer Download and Install git clone https://github.com/stefankumpan/Image-Optimizer-Script.git cd Image-Optimizer-Script pip install -r req

PyTorch implementation of Constrained Policy Optimization (CPO) This repository has a simple to understand and use implementation of CPO in PyTorch. A

This repository contains the code accompanying the paper " FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation" Paper link: R

ttopt Description Gradient-free global optimization algorithm for multidimensional functions based on the low rank tensor train (TT) format and maximu

Lale is a Python library for semi-automated data science. Lale makes it easy to automatically select algorithms and tune hyperparameters of pipelines that are compatible with scikit-learn, in a type-safe fashion.

BO-GP Bayesian optimization based on Gaussian processes (BO-GP) for CFD simulations. The BO-GP codes are developed using GPy and GPyOpt. The optimizer

ETMO: Evolutionary Transfer Multiobjective Optimization To promote the research on ETMO, benchmark problems are of great importance to ETMO algorithm

STRIDE: spectrahedral proximal gradient descent along vertices A Solver for Large-Scale Rank-One Semidefinite Relaxations About STRIDE is designed for

A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

Nature-inspired algorithms are a very popular tool for solving optimization problems. Numerous variants of nature-inspired algorithms have been develo

Description A numpy-based implementation of RANSAC for fundamental matrix and homography estimation. The degeneracy updating and local optimization co

CONetV2: Efficient Auto-Channel Size Optimization for CNNs Exciting News! CONetV2: Efficient Auto-Channel Size Optimization for CNNs has been accepted

Information-Theoretic Multi-Objective Bayesian Optimization with Continuous Approximations Requirements The code is implemented in Python and requires

DeepSeaTreasure Environment Installation In order to get started with this environment, you can install it using the following command: python3 -m pip

hyperpy HyperPy: An automatic hyperparameter optimization framework Description HyperPy: Library for automatic hyperparameter optimization. Build on t

Network-Distributed Algorithm Experiments -- This repository contains a set of optimization algorithms and objective functions, and all code needed to

OptaPy is an AI constraint solver for Python to optimize the Vehicle Routing Problem, Employee Rostering, Maintenance Scheduling, Task Assignment, School Timetabling, Cloud Optimization, Conference Scheduling, Job Shop Scheduling, Bin Packing and many more planning problems.

Taichi TopOpt (Under Active Development) Intro A topology optimization framework written in Taichi programming language, which is embedded in Python.