441 Repositories
Python trust-region-policy-optimization Libraries
Adversarial Texture Optimization from RGB-D Scans (CVPR 2020).
AdversarialTexture Adversarial Texture Optimization from RGB-D Scans (CVPR 2020). Scanning Data Download Please refer to data directory for details. B
WORD: Revisiting Organs Segmentation in the Whole Abdominal Region
WORD: Revisiting Organs Segmentation in the Whole Abdominal Region (Paper and DataSet). [New] Note that all the emails about the download permission o
scikit-learn models hyperparameters tuning and feature selection, using evolutionary algorithms.
Sklearn-genetic-opt scikit-learn models hyperparameters tuning and feature selection, using evolutionary algorithms. This is meant to be an alternativ
NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.
The source code is temporariy removed, as we are solving potential copyright and license issues with GRANSO (http://www.timmitchell.com/software/GRANS
Noto fonts go universal! Download Noto fonts combined to suit your region
noto-cjk Noto CJK fonts Noto Serif CJK update was released on 25 October 2021. We moved the release history and other notes into both Sans and Serif s
A Transformer-Based Feature Segmentation and Region Alignment Method For UAV-View Geo-Localization
University1652-Baseline [Paper] [Slide] [Explore Drone-view Data] [Explore Satellite-view Data] [Explore Street-view Data] [Video Sample] [中文介绍] This
Pretrained language model and its related optimization techniques developed by Huawei Noah's Ark Lab.
Pretrained Language Model This repository provides the latest pretrained language models and its related optimization techniques developed by Huawei N
[TPDS'21] COSCO: Container Orchestration using Co-Simulation and Gradient Based Optimization for Fog Computing Environments
COSCO Framework COSCO is an AI based coupled-simulation and container orchestration framework for integrated Edge, Fog and Cloud Computing Environment
Simulation and Parameter Estimation in Geophysics
Simulation and Parameter Estimation in Geophysics - A python package for simulation and gradient based parameter estimation in the context of geophysical applications.
PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
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.
NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.
Code, environments, and scripts for the paper: "How Private Is Your RL Policy? An Inverse RL Based Analysis Framework"
Privacy-Aware Inverse RL (PRIL) Analysis Framework Code, environments, and scripts for the paper: "How Private Is Your RL Policy? An Inverse RL Based
1st Solution For NeurIPS 2021 Competition on ML4CO Dual Task
KIDA: Knowledge Inheritance in Data Aggregation This project releases our 1st place solution on NeurIPS2021 ML4CO Dual Task. Slide and model weights a
A simple CLI tool for getting region-specific status of Logz.io components.
About A simple CLI tool for checking the current status of Logz.io components per region. Built With Python 3 The following packeges (see requirements
Security Monkey monitors AWS, GCP, OpenStack, and GitHub orgs for assets and their changes over time.
NOTE: Security Monkey is in maintenance mode and will be end-of-life in 2020. For AWS users, please make use of AWS Config. For GCP users, please make
[NeurIPS 2021] Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects
[NeurIPS 2021] Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects YouTube | arXiv Prerequisites Kaolin is available here:
A simple and lightweight genetic algorithm for optimization of any machine learning model
geneticml This package contains a simple and lightweight genetic algorithm for optimization of any machine learning model. Installation Use pip to ins
CALVIN - A benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks
CALVIN CALVIN - A benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks Oier Mees, Lukas Hermann, Erick Rosete,
Pretrained Cost Model for Distributed Constraint Optimization Problems
Pretrained Cost Model for Distributed Constraint Optimization Problems Requirements PyTorch 1.9.0 PyTorch Geometric 1.7.1 Directory structure baseline
A simple and lightweight genetic algorithm for optimization of any machine learning model
geneticml This package contains a simple and lightweight genetic algorithm for optimization of any machine learning model. Installation Use pip to ins
Active Offline Policy Selection With Python
Active Offline Policy Selection This is supporting example code for NeurIPS 2021 paper Active Offline Policy Selection by Ksenia Konyushkova*, Yutian
Enhancing Twin Delayed Deep Deterministic Policy Gradient with Cross-Entropy Method
Enhancing Twin Delayed Deep Deterministic Policy Gradient with Cross-Entropy Method Hieu Trung Nguyen, Khang Tran and Ngoc Hoang Luong Setup Clone thi
FedTorch is an open-source Python package for distributed and federated training of machine learning models using PyTorch distributed API
FedTorch is a generic repository for benchmarking different federated and distributed learning algorithms using PyTorch Distributed API.
FuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space OptimizationFuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space Optimization
FuseDream This repo contains code for our paper (paper link): FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimizat
Python implementation of Bayesian optimization over permutation spaces.
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
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
slientruss3d : Python for stable truss analysis tool Desciption slientruss3d is a python package which can solve the resistances, internal forces and
A library for differentiable nonlinear optimization.
Theseus A library for differentiable nonlinear optimization built on PyTorch to support constructing various problems in robotics and vision as end-to
PyTorch implementation of Decoupling Value and Policy for Generalization in Reinforcement Learning
PyTorch implementation of Decoupling Value and Policy for Generalization in Reinforcement Learning
Reviatalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation
Reviatalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation This is the implementation of the approach describ
PyTorch implementation of Off-policy Learning in Two-stage Recommender Systems
Off-Policy-2-Stage This repo provides a PyTorch implementation of the MovieLens experiments for the following paper: Off-policy Learning in Two-stage
Prototypical python implementation of the trust-region algorithm presented in Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints by Larson, Leyffer, Kirches, and Manns.
Prototypical python implementation of the trust-region algorithm presented in Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints by Larson, Leyffer, Kirches, and Manns.
Milano is a tool for automating hyper-parameters search for your models on a backend of your choice.
Milano (This is a research project, not an official NVIDIA product.) Documentation https://nvidia.github.io/Milano Milano (Machine learning autotuner
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
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 and its related optimization techniques developed by Huawei Noah's Ark Lab.
Pretrained Language Model This repository provides the latest pretrained language models and its related optimization techniques developed by Huawei N
Official Repository for "Robust On-Policy Data Collection for Data Efficient Policy Evaluation" (NeurIPS 2021 Workshop on OfflineRL).
Robust On-Policy Data Collection for Data-Efficient Policy Evaluation Source code of Robust On-Policy Data Collection for Data-Efficient Policy Evalua
Official repository for: Continuous Control With Ensemble DeepDeterministic Policy Gradients
Continuous Control With Ensemble Deep Deterministic Policy Gradients This repository is the official implementation of Continuous Control With Ensembl
PyTorch implementation of the TTC algorithm
Trust-the-Critics This repository is a PyTorch implementation of the TTC algorithm and the WGAN misalignment experiments presented in Trust the Critic
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-Learning
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-Learning This is the official repository of "Camera Distortion-
A semismooth Newton method for elliptic PDE-constrained optimization
sNewton4PDEOpt The Python module implements a semismooth Newton method for solving finite-element discretizations of the strongly convex, linear ellip
⚡️Optimizing einsum functions in NumPy, Tensorflow, Dask, and more with contraction order optimization.
Optimized Einsum Optimized Einsum: A tensor contraction order optimizer Optimized einsum can significantly reduce the overall execution time of einsum
Implementation of Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning
advantage-weighted-regression Implementation of Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning, by Peng et al. (
Algorithmic trading backtest and optimization examples using order book imbalances. (bitcoin, cryptocurrency, bitmex)
Algorithmic trading backtest and optimization examples using order book imbalances. (bitcoin, cryptocurrency, bitmex)
A Python project for optimizing the 8 Queens Puzzle using the Genetic Algorithm implemented in PyGAD.
8QueensGenetic A Python project for optimizing the 8 Queens Puzzle using the Genetic Algorithm implemented in PyGAD. The project uses the Kivy cross-p
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
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
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
Training code and evaluation benchmarks for the "Self-Supervised Policy Adaptation during Deployment" paper.
Self-Supervised Policy Adaptation during Deployment PyTorch implementation of PAD and evaluation benchmarks from Self-Supervised Policy Adaptation dur
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
Region-aware Contrastive Learning for Semantic Segmentation, ICCV 2021
Region-aware Contrastive Learning for Semantic Segmentation, ICCV 2021 Abstract Recent works have made great success in semantic segmentation by explo
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
A Python package for causal inference using Synthetic Controls
Synthetic Control Methods A Python package for causal inference using synthetic controls This Python package implements a class of approaches to estim
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
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.
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
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
Multiple implementations for abstractive text summurization , using google colab
Text Summarization models if you are able to endorse me on Arxiv, i would be more than glad https://arxiv.org/auth/endorse?x=FRBB89 thanks This repo i
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
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
Source code for our paper "Do Not Trust Prediction Scores for Membership Inference Attacks"
Do Not Trust Prediction Scores for Membership Inference Attacks Abstract: Membership inference attacks (MIAs) aim to determine whether a specific samp
Implementation of Sequence Generative Adversarial Nets with Policy Gradient
SeqGAN Requirements: Tensorflow r1.0.1 Python 2.7 CUDA 7.5+ (For GPU) Introduction Apply Generative Adversarial Nets to generating sequences of discre
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
Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting
Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting
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
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
Mengzhan (John) code for Closed Loop Control system of Sharp Wave Ripples in Hippocampus CA3 region
ClosedLoopControl_Yu Mengzhan (John) code for Closed Loop Control system of Sharp Wave Ripples in Hippocampus CA3 region Creating Python Virtual Envir
MagTape is a Policy-as-Code tool for Kubernetes that allows for evaluating Kubernetes resources against a set of defined policies to inform and enforce best practice configurations.
MagTape is a Policy-as-Code tool for Kubernetes that allows for evaluating Kubernetes resources against a set of defined policies to inform and enforce best practice configurations. MagTape includes variable policy enforcement, notifications, and targeted metrics.
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
Multi-objective constrained optimization for energy applications via tree ensembles
Multi-objective constrained optimization for energy applications via tree ensembles
Gym environments used in the paper: "Developmental Reinforcement Learning of Control Policy of a Quadcopter UAV with Thrust Vectoring Rotors"
gym_multirotor Gym to train reinforcement learning agents on UAV platforms Quadrotor Tiltrotor Requirements This package has been tested on Ubuntu 18.
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
6D Grasping Policy for Point Clouds
GA-DDPG [website, paper] Installation git clone https://github.com/liruiw/GA-DDPG.git --recursive Setup: Ubuntu 16.04 or above, CUDA 10.0 or above, py
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
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
'A C2C E-COMMERCE TRUST MODEL BASED ON REPUTATION' Python implementation
Project description A library providing functionalities to calculate reputation and degree of trust on C2C ecommerce platforms. The work is fully base
WORD: Revisiting Organs Segmentation in the Whole Abdominal Region
WORD: Revisiting Organs Segmentation in the Whole Abdominal Region. This repository provides the codebase and dataset for our work WORD: Revisiting Or
A method to perform unsupervised cross-region adaptation of crop classifiers trained with satellite image time series.
TimeMatch Official source code of TimeMatch: Unsupervised Cross-region Adaptation by Temporal Shift Estimation by Joachim Nyborg, Charlotte Pelletier,
Trains an agent with stochastic policy gradient ascent to solve the Lunar Lander challenge from OpenAI
Introduction This script trains an agent with stochastic policy gradient ascent to solve the Lunar Lander challenge from OpenAI. In order to run this
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