441 Repositories
Python trust-region-policy-optimization Libraries
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
This tool allows to automatically test for Content Security Policy bypass payloads.
CSPass This tool allows to automatically test for Content Security Policy bypass payloads. Usage [cspass]$ ./cspass.py -h usage: cspass.py [-h] [--no-
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 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
The official code repository for NeurIPS 2021 paper "Unsupervised Foreground Extraction via Deep Region Competition".
Unsupervised Foreground Extraction via Deep Region Competition [Paper] [Code] The official code repository for NeurIPS 2021 paper "Unsupervised Foregr
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
Unsupervised Foreground Extraction via Deep Region Competition
Unsupervised Foreground Extraction via Deep Region Competition [Paper] [Code] The official code repository for NeurIPS 2021 paper "Unsupervised Foregr
🔥 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.
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).
Off-policy continuous control in PyTorch, with RDPG, RTD3 & RSAC
arXiv technical report soon available. we are updating the readme to be as comprehensive as possible Please ask any questions in Issues, thanks. Intro
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
Set the draft security HTTP header Permissions-Policy (previously Feature-Policy) on your Django app.
django-permissions-policy Set the draft security HTTP header Permissions-Policy (previously Feature-Policy) on your Django app. Requirements Python 3.
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.
Time Discretization-Invariant Safe Action Repetition for Policy Gradient Methods
Time Discretization-Invariant Safe Action Repetition for Policy Gradient Methods This repository is the official implementation of Seohong Park, Jaeky
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
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
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
Retentioneering: product analytics, data-driven customer journey map optimization, marketing analytics, web analytics, transaction analytics, graph visualization, and behavioral segmentation with customer segments in Python.
What is Retentioneering? Retentioneering is a Python framework and library to assist product analysts and marketing analysts as it makes it easier to
MBPO (paper: When to trust your model: Model-based policy optimization) in offline RL settings
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
Deep Reinforcement Learning by using an on-policy adaptation of Maximum a Posteriori Policy Optimization (MPO)
V-MPO Simple code to demonstrate Deep Reinforcement Learning by using an on-policy adaptation of Maximum a Posteriori Policy Optimization (MPO) in Pyt
Official PyTorch implementation of "Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient".
Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient This repository is the official PyTorch implementation of "Edge Rewiring Go
A library for optimization on Riemannian manifolds
TensorFlow RiemOpt A library for manifold-constrained optimization in TensorFlow. Installation To install the latest development version from GitHub:
Python Image Optimizer Script
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
PyTorch implementation of Constrained Policy Optimization (CPO) This repository has a simple to understand and use implementation of CPO in PyTorch. A
FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation
This repository contains the code accompanying the paper " FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation" Paper link: R
Gradient-free global optimization algorithm for multidimensional functions based on the low rank tensor train format
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 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.
Bayesian optimization based on Gaussian processes (BO-GP) for CFD simulations.
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
ETMO: Evolutionary Transfer Multiobjective Optimization To promote the research on ETMO, benchmark problems are of great importance to ETMO algorithm
Solver for Large-Scale Rank-One Semidefinite Relaxations
STRIDE: spectrahedral proximal gradient descent along vertices A Solver for Large-Scale Rank-One Semidefinite Relaxations About STRIDE is designed for
ProMP: Proximal Meta-Policy Search
ProMP: Proximal Meta-Policy Search Implementations corresponding to ProMP (Rothfuss et al., 2018). Overall this repository consists of two branches: m
Hypernets: A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.
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.
Nature-inspired algorithms are a very popular tool for solving optimization problems. Numerous variants of nature-inspired algorithms have been develo
A numpy-based implementation of RANSAC for fundamental matrix and homography estimation. The degeneracy updating and local optimization components are included and optional.
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
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
Information-Theoretic Multi-Objective Bayesian Optimization with Continuous Approximations Requirements The code is implemented in Python and requires
Deep Sea Treasure Environment for Multi-Objective Optimization Research
DeepSeaTreasure Environment Installation In order to get started with this environment, you can install it using the following command: python3 -m pip
CAPITAL: Optimal Subgroup Identification via Constrained Policy Tree Search
CAPITAL: Optimal Subgroup Identification via Constrained Policy Tree Search This repository is the official implementation of CAPITAL: Optimal Subgrou
HyperaPy: An automatic hyperparameter optimization framework ⚡🚀
hyperpy HyperPy: An automatic hyperparameter optimization framework Description HyperPy: Library for automatic hyperparameter optimization. Build on t
BasicRL: easy and fundamental codes for deep reinforcement learning。It is an improvement on rainbow-is-all-you-need and OpenAI Spinning Up.
BasicRL: easy and fundamental codes for deep reinforcement learning BasicRL is an improvement on rainbow-is-all-you-need and OpenAI Spinning Up. It is
Code for the paper SphereRPN: Learning Spheres for High-Quality Region Proposals on 3D Point Clouds Object Detection, ICIP 2021.
SphereRPN Code for the paper SphereRPN: Learning Spheres for High-Quality Region Proposals on 3D Point Clouds Object Detection, ICIP 2021. Authors: Th
Experiments for distributed optimization algorithms
Network-Distributed Algorithm Experiments -- This repository contains a set of optimization algorithms and objective functions, and all code needed to
Simple Python tool that generates a pseudo-random password with numbers, letters, and special characters in accordance with password policy best practices.
Simple Python tool that generates a pseudo-random password with numbers, letters, and special characters in accordance with password policy best practices.
OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems.
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.
A topology optimization framework written in Taichi programming language, which is embedded in Python.
Taichi TopOpt (Under Active Development) Intro A topology optimization framework written in Taichi programming language, which is embedded in Python.
Fast batch image resizer and rotator for JPEG and PNG images.
imgp is a command line image resizer and rotator for JPEG and PNG images.
Official Implementation of 'UPDeT: Universal Multi-agent Reinforcement Learning via Policy Decoupling with Transformers' ICLR 2021(spotlight)
UPDeT Official Implementation of UPDeT: Universal Multi-agent Reinforcement Learning via Policy Decoupling with Transformers (ICLR 2021 spotlight) The
A Python Package for Portfolio Optimization using the Critical Line Algorithm
A Python Package for Portfolio Optimization using the Critical Line Algorithm
Wonk is a tool for combining a set of AWS policy files into smaller compiled policy sets.
Wonk is a tool for combining a set of AWS policy files into smaller compiled policy sets.
A Python Package for Portfolio Optimization using the Critical Line Algorithm
PyCLA A Python Package for Portfolio Optimization using the Critical Line Algorithm Getting started To use PyCLA, clone the repo and install the requi
OptNet: Differentiable Optimization as a Layer in Neural Networks
OptNet: Differentiable Optimization as a Layer in Neural Networks This repository is by Brandon Amos and J. Zico Kolter and contains the PyTorch sourc
Riemannian Adaptive Optimization Methods with pytorch optim
geoopt Manifold aware pytorch.optim. Unofficial implementation for “Riemannian Adaptive Optimization Methods” ICLR2019 and more. Installation Make sur
ppo_pytorch_cpp - an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch
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 Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286
Pytorch-DPPO Pytorch implementation of Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286 Using PPO with clip loss (from https
easyopt is a super simple yet super powerful optuna-based Hyperparameters Optimization Framework that requires no coding.
easyopt is a super simple yet super powerful optuna-based Hyperparameters Optimization Framework that requires no coding.
Implementation of algorithms for continuous control (DDPG and NAF).
DEPRECATION This repository is deprecated and is no longer maintaned. Please see a more recent implementation of RL for continuous control at jax-sac.
OptNet: Differentiable Optimization as a Layer in Neural Networks
OptNet: Differentiable Optimization as a Layer in Neural Networks This repository is by Brandon Amos and J. Zico Kolter and contains the PyTorch sourc
Task-based end-to-end model learning in stochastic optimization
Task-based End-to-end Model Learning in Stochastic Optimization This repository is by Priya L. Donti, Brandon Amos, and J. Zico Kolter and contains th
Demonstration that AWS IAM policy evaluation docs are incorrect
The flowchart from the AWS IAM policy evaluation documentation page, as of 2021-09-12, and dating back to at least 2018-12-27, is the following: The f
Official PyTorch code of DeepPanoContext: Panoramic 3D Scene Understanding with Holistic Scene Context Graph and Relation-based Optimization (ICCV 2021 Oral).
DeepPanoContext (DPC) [Project Page (with interactive results)][Paper] DeepPanoContext: Panoramic 3D Scene Understanding with Holistic Scene Context G
Certifiable Outlier-Robust Geometric Perception
Certifiable Outlier-Robust Geometric Perception About This repository holds the implementation for certifiably solving outlier-robust geometric percep
Find information about an IP address, such as its location, ISP, hostname, region, country, and city.
Find information about an IP address, such as its location, ISP, hostname, region, country, and city. An IP address can be traced, tracked, and located.
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 network.
GNPy: Optical Route Planning and DWDM Network Optimization
GNPy is an open-source, community-developed library for building route planning and optimization tools in real-world mesh optical networks
OptaPlanner wrappers for Python. Currently significantly slower than OptaPlanner in Java or Kotlin.
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.
Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation
Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation The code of: Cross-Image Region Mining with Region Proto
Extract and visualize information from Gurobi log files
GRBlogtools Extract information from Gurobi log files and generate pandas DataFrames or Excel worksheets for further processing. Also includes a wrapp
Automated Hyperparameter Optimization Competition
QQ浏览器2021AI算法大赛 - 自动超参数优化竞赛 ACM CIKM 2021 AnalyticCup 在信息流推荐业务场景中普遍存在模型或策略效果依赖于“超参数”的问题,而“超参数"的设定往往依赖人工经验调参,不仅效率低下维护成本高,而且难以实现更优效果。因此,本次赛题以超参数优化为主题,从真
PPO is a very popular Reinforcement Learning algorithm at present.
PPO is a very popular Reinforcement Learning algorithm at present. OpenAI takes PPO as the current baseline algorithm. We use the PPO algorithm to train a policy to give the best action in any situation.
Code for EMNLP 2021 main conference paper "Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification"
Code for EMNLP 2021 main conference paper "Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification"
Code for EMNLP 2021 main conference paper "Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification"
Text-AutoAugment (TAA) This repository contains the code for our paper Text AutoAugment: Learning Compositional Augmentation Policy for Text Classific
scrilla: A Financial Optimization Application
A python application that wraps around AlphaVantage, Quandl and IEX APIs, calculates financial statistics and optimizes portfolio allocations.
AWSXenos will list all the trust relationships in all the IAM roles and S3 buckets
AWS External Account Scanner Xenos, is Greek for stranger. AWSXenos will list all the trust relationships in all the IAM roles, and S3 buckets, in an
An efficient framework for reinforcement learning.
rl: An efficient framework for reinforcement learning Requirements Introduction PPO Test Requirements name version Python =3.7 numpy =1.19 torch =1
[ICCV 2021 Oral] NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo
NerfingMVS Project Page | Paper | Video | Data NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo Yi Wei, Shaohui
Official implementation of the MM'21 paper Constrained Graphic Layout Generation via Latent Optimization
[MM'21] Constrained Graphic Layout Generation via Latent Optimization This repository provides the official code for the paper "Constrained Graphic La
ICCV2021 Oral SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks
Sign-Agnostic Convolutional Occupancy Networks Paper | Supplementary | Video | Teaser Video | Project Page This repository contains the implementation
[ICCV 2021] Official Pytorch implementation for Discriminative Region-based Multi-Label Zero-Shot Learning SOTA results on NUS-WIDE and OpenImages
Discriminative Region-based Multi-Label Zero-Shot Learning (ICCV 2021) [arXiv][Project page coming soon] Sanath Narayan*, Akshita Gupta*, Salman Kh
Differentiable Factor Graph Optimization for Learning Smoothers @ IROS 2021
Differentiable Factor Graph Optimization for Learning Smoothers Overview Status Setup Datasets Training Evaluation Acknowledgements Overview Code rele
[ICCV 2021] Official Pytorch implementation for Discriminative Region-based Multi-Label Zero-Shot Learning SOTA results on NUS-WIDE and OpenImages
Discriminative Region-based Multi-Label Zero-Shot Learning (ICCV 2021) [arXiv][Project page coming soon] Sanath Narayan*, Akshita Gupta*, Salman Kh
PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning.
neural-combinatorial-rl-pytorch PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning. I have implemented the basic
Pytorch implementation of Distributed Proximal Policy Optimization
Pytorch-DPPO Pytorch implementation of Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286 Using PPO with clip loss (from https
ICCV2021 Oral SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks
Sign-Agnostic Convolutional Occupancy Networks Paper | Supplementary | Video | Teaser Video | Project Page This repository contains the implementation