195 Repositories
Python actor-critic-methods Libraries
MRI reconstruction (e.g., QSM) using deep learning methods
deepMRI: Deep learning methods for MRI Authors: Yang Gao, Hongfu Sun This repo is devloped based on Pytorch (1.8 or later) and matlab (R2019a or later
A criticism of a recent paper on buggy image downsampling methods in popular image processing and deep learning libraries.
A criticism of a recent paper on buggy image downsampling methods in popular image processing and deep learning libraries.
[NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods Large Scale Learning on Non-Homophilous Graphs: New Benchmark
Collection Of Discord Hacking Tools / Fun Stuff / Exploits That Is Completely Made Using Python.
Venom Collection Of Discord Hacking Tools / Fun Stuff / Exploits That Is Completely Made Using Python. Report Bug · Request Feature Contributing Well,
This codebase proposes modular light python and pytorch implementations of several LiDAR Odometry methods
pyLiDAR-SLAM This codebase proposes modular light python and pytorch implementations of several LiDAR Odometry methods, which can easily be evaluated
A collection of differentiable SVD methods and also the official implementation of the ICCV21 paper "Why Approximate Matrix Square Root Outperforms Accurate SVD in Global Covariance Pooling?"
Differentiable SVD Introduction This repository contains: The official Pytorch implementation of ICCV21 paper Why Approximate Matrix Square Root Outpe
[NeurIPS'21] Shape As Points: A Differentiable Poisson Solver
Shape As Points (SAP) Paper | Project Page | Short Video (6 min) | Long Video (12 min) This repository contains the implementation of the paper: Shape
Code repository for EMNLP 2021 paper 'Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods'
Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods This is the code repository to accompany the EMNLP 2021 paper on ad
Road Crack Detection Using Deep Learning Methods
Road-Crack-Detection-Using-Deep-Learning-Methods This is my Diploma Thesis ¨Road Crack Detection Using Deep Learning Methods¨ under the supervision of
Svector (pronounced Swag-tor) provides extension methods to pyrsistent data structures
Svector Svector (pronounced Swag-tor) provides extension methods to pyrsistent data structures. Easily chain your methods confidently with tons of add
Reddit comment bot emulating Telugu actor N. Bala Krishna.
Balayya-Bot Reddit comment bot emulating Telugu actor N. Bala Krishna. Project structure config.py contains Bot's higher level configuration. generate
LegalNLP - Natural Language Processing Methods for the Brazilian Legal Language
LegalNLP - Natural Language Processing Methods for the Brazilian Legal Language ⚖️ The library of Natural Language Processing for Brazilian legal lang
Some methods for comparing network representations in deep learning and neuroscience.
Generalized Shape Metrics on Neural Representations In neuroscience and in deep learning, quantifying the (dis)similarity of neural representations ac
Python @deprecat decorator to deprecate old python classes, functions or methods.
deprecat Decorator Python @deprecat decorator to deprecate old python classes, functions or methods. Installation pip install deprecat Usage To use th
A Comprehensive Study on Learning-Based PE Malware Family Classification Methods
A Comprehensive Study on Learning-Based PE Malware Family Classification Methods Datasets Because of copyright issues, both the MalwareBazaar dataset
[NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods Large Scale Learning on Non-Homophilous Graphs: New Benchmark
Source code for the NeurIPS 2021 paper "On the Second-order Convergence Properties of Random Search Methods"
Second-order Convergence Properties of Random Search Methods This repository the paper "On the Second-order Convergence Properties of Random Search Me
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).
This repository contains code demonstrating the methods outlined in Path Signature Area-Based Causal Discovery in Coupled Time Series presented at Causal Analysis Workshop 2021.
signed-area-causal-inference This repository contains code demonstrating the methods outlined in Path Signature Area-Based Causal Discovery in Coupled
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
Spatiotemporal resampling methods for mlr3
mlr3spatiotempcv Package website: release | dev Spatiotemporal resampling methods for mlr3. This package extends the mlr3 package framework with spati
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
Numerical methods for ordinary differential equations: Euler, Improved Euler, Runge-Kutta.
Numerical methods Numerical methods for ordinary differential equations are methods used to find numerical approximations to the solutions of ordinary
Official Pytorch implementation of the paper "Action-Conditioned 3D Human Motion Synthesis with Transformer VAE", ICCV 2021
ACTOR Official Pytorch implementation of the paper "Action-Conditioned 3D Human Motion Synthesis with Transformer VAE", ICCV 2021. Please visit our we
High-quality implementations of standard and SOTA methods on a variety of tasks.
Uncertainty Baselines The goal of Uncertainty Baselines is to provide a template for researchers to build on. The baselines can be a starting point fo
Continual reinforcement learning baselines: experiment specifications, implementation of existing methods, and common metrics. Easily extensible to new methods.
Continual Reinforcement Learning This repository provides a simple way to run continual reinforcement learning experiments in PyTorch, including evalu
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
Composing methods for ML training efficiency
MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training.
Python Library for Signal/Image Data Analysis with Transport Methods
PyTransKit Python Transport Based Signal Processing Toolkit Website and documentation: https://pytranskit.readthedocs.io/ Installation The library cou
Semi-Supervised Signed Clustering Graph Neural Network (and Implementation of Some Spectral Methods)
SSSNET SSSNET: Semi-Supervised Signed Network Clustering For details, please read our paper. Environment Setup Overview The project has been tested on
MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training
MosaicML Composer MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training. We aim to ease th
A brand new hub for Scene Graph Generation methods based on MMdetection (2021). The pipeline of from detection, scene graph generation to downstream tasks (e.g., image cpationing) is supported. Pytorch version implementation of HetH (ECCV 2020) and TopicSG (ICCV 2021) is included.
MMSceneGraph Introduction MMSceneneGraph is an open source code hub for scene graph generation as well as supporting downstream tasks based on the sce
Implementation of temporal pooling methods studied in [ICIP'20] A Comparative Evaluation Of Temporal Pooling Methods For Blind Video Quality Assessment
Implementation of temporal pooling methods studied in [ICIP'20] A Comparative Evaluation Of Temporal Pooling Methods For Blind Video Quality Assessment
Scientific Computation Methods in C and Python (Open for Hacktoberfest 2021)
Sci - cpy README is a stub. Do expand it. Objective This repository is meant to be a ready reference for scientific computation methods. Do ⭐ it if yo
Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM
Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Comprehensive collection of Pixel Attribution methods for Computer Vision.
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
Code for paper "Which Training Methods for GANs do actually Converge? (ICML 2018)"
GAN stability This repository contains the experiments in the supplementary material for the paper Which Training Methods for GANs do actually Converg
Apply Graph Self-Supervised Learning methods to graph-level task(TUDataset, MolculeNet Datset)
Graphlevel-SSL Overview Apply Graph Self-Supervised Learning methods to graph-level task(TUDataset, MolculeNet Dataset). It is unified framework to co
PyTorch implementation of Advantage async actor-critic Algorithms (A3C) in PyTorch
Advantage async actor-critic Algorithms (A3C) in PyTorch @inproceedings{mnih2016asynchronous, title={Asynchronous methods for deep reinforcement lea
LeafSnap replicated using deep neural networks to test accuracy compared to traditional computer vision methods.
Deep-Leafsnap Convolutional Neural Networks have become largely popular in image tasks such as image classification recently largely due to to Krizhev
Deep Reinforcement Learning with pytorch & visdom
Deep Reinforcement Learning with pytorch & visdom Sample testings of trained agents (DQN on Breakout, A3C on Pong, DoubleDQN on CartPole, continuous A
Asynchronous Advantage Actor-Critic in PyTorch
Asynchronous Advantage Actor-Critic in PyTorch This is PyTorch implementation of A3C as described in Asynchronous Methods for Deep Reinforcement Learn
The project is investigating methods to extract human-marked data from document forms such as surveys and tests.
The project is investigating methods to extract human-marked data from document forms such as surveys and tests. They can read questions, multiple-choice exam papers, and grade.
[EMNLP 2021] LM-Critic: Language Models for Unsupervised Grammatical Error Correction
LM-Critic: Language Models for Unsupervised Grammatical Error Correction This repo provides the source code & data of our paper: LM-Critic: Language M
Factoral Methods using two different method
Factoral-Methods-using-two-different-method Here, I am finding the factorial of a number by using two different method. The first method is by using f
Here, I have discuss the three methods of list reversion. The three methods are built-in method, slicing method and position changing method.
Three-different-method-for-list-reversion Here, I have discuss the three methods of list reversion. The three methods are built-in method, slicing met
Find existing email addresses by nickname using API/SMTP checking methods without user notification. Please, don't hesitate to improve cat's job! 🐱🔎 📬
mailcat The only cat who can find existing email addresses by nickname. Usage First install requirements: pip3 install -r requirements.txt Then just
Simulation of the solar system using various nummerical methods
solar-system Simulation of the solar system using various nummerical methods Download the repo Make shure matplotlib, scipy etc. are installed execute
Selene is a Python library and command line interface for training deep neural networks from biological sequence data such as genomes.
Selene is a Python library and command line interface for training deep neural networks from biological sequence data such as genomes.
A3C LSTM Atari with Pytorch plus A3G design
NEWLY ADDED A3G A NEW GPU/CPU ARCHITECTURE OF A3C FOR SUBSTANTIALLY ACCELERATED TRAINING!! RL A3C Pytorch NEWLY ADDED A3G!! New implementation of A3C
Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM
Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Tested on many Common CNN Networks and Vision Transformers. ⭐ Includes smoo
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-a2c-ppo-acktr Update (April 12th, 2021) PPO is great, but Soft Actor Critic can be better for many continuous control tasks. Please check out
Active Directory Penetration Testing methods with simulations
AD penetration Testing Project By Ruben Enkaoua - GL4Di4T0R Based on the TCM PEH course (Heath Adams) Index 1 - Setting Up the Lab Intallation of a Wi
We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.
An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering Papers with code | Paper Nikola Zubić Pietro Lio University
Combines power of torch, numerical methods to conquer and solve ALL {O,P}DEs
torch_DE_solver Combines power of torch, numerical methods and math overall to conquer and solve ALL {O,P}DEs There are three examples to provide a li
Code for paper "Which Training Methods for GANs do actually Converge? (ICML 2018)"
GAN stability This repository contains the experiments in the supplementary material for the paper Which Training Methods for GANs do actually Converg
Pandas and Dask test helper methods with beautiful error messages.
beavis Pandas and Dask test helper methods with beautiful error messages. test helpers These test helper methods are meant to be used in test suites.
Implement A3C for Mujoco gym envs
pytorch-a3c-mujoco Disclaimer: my implementation right now is unstable (you ca refer to the learning curve below), I'm not sure if it's my problems. A
A PyTorch-based open-source framework that provides methods for improving the weakly annotated data and allows researchers to efficiently develop and compare their own methods.
Knodle (Knowledge-supervised Deep Learning Framework) - a new framework for weak supervision with neural networks. It provides a modularization for se
ElegantRL is featured with lightweight, efficient and stable, for researchers and practitioners.
Lightweight, efficient and stable implementations of deep reinforcement learning algorithms using PyTorch. 🔥
This is the official repository for evaluation on the NoW Benchmark Dataset. The goal of the NoW benchmark is to introduce a standard evaluation metric to measure the accuracy and robustness of 3D face reconstruction methods from a single image under variations in viewing angle, lighting, and common occlusions.
NoW Evaluation This is the official repository for evaluation on the NoW Benchmark Dataset. The goal of the NoW benchmark is to introduce a standard e
Exploration-Exploitation Dilemma Solving Methods
Exploration-Exploitation Dilemma Solving Methods Medium article for this repo - HERE In ths repo I implemented two techniques for tackling mentioned t
An integration of several popular automatic augmentation methods, including OHL (Online Hyper-Parameter Learning for Auto-Augmentation Strategy) and AWS (Improving Auto Augment via Augmentation Wise Weight Sharing) by Sensetime Research.
An integration of several popular automatic augmentation methods, including OHL (Online Hyper-Parameter Learning for Auto-Augmentation Strategy) and AWS (Improving Auto Augment via Augmentation Wise Weight Sharing) by Sensetime Research.
Small Python library that adds password hashing methods to ORM objects
Password Mixin Mixin that adds some useful methods to ORM objects Compatible with Python 3.5 = 3.9 Install pip install password-mixin Setup first cre
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [2021]
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations This repo contains the Pytorch implementation of our paper: Revisit
JAX code for the paper "Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation"
Optimal Model Design for Reinforcement Learning This repository contains JAX code for the paper Control-Oriented Model-Based Reinforcement Learning wi
Package pyVHR is a comprehensive framework for studying methods of pulse rate estimation relying on remote photoplethysmography (rPPG)
Package pyVHR (short for Python framework for Virtual Heart Rate) is a comprehensive framework for studying methods of pulse rate estimation relying on remote photoplethysmography (rPPG)
Solve various integral equations using numerical methods in Python
Solve Volterra and Fredholm integral equations This Python package estimates Volterra and Fredholm integral equations using known techniques. Installa
PyTorch CZSL framework containing GQA, the open-world setting, and the CGE and CompCos methods.
Compositional Zero-Shot Learning This is the official PyTorch code of the CVPR 2021 works Learning Graph Embeddings for Compositional Zero-shot Learni
Paddle-RLBooks is a reinforcement learning code study guide based on pure PaddlePaddle.
Paddle-RLBooks Welcome to Paddle-RLBooks which is a reinforcement learning code study guide based on pure PaddlePaddle. 欢迎来到Paddle-RLBooks,该仓库主要是针对强化学
🏭 An easy-to-use implementation of Creation Methods for Django, backed by Faker.
Django-fakery An easy-to-use implementation of Creation Methods (aka Object Factory) for Django, backed by Faker. django_fakery will try to guess the
This is the dataset for testing the robustness of various VO/VIO methods
KAIST VIO dataset This is the dataset for testing the robustness of various VO/VIO methods You can download the whole dataset on KAIST VIO dataset Ind
PyTorch implementation of the end-to-end coreference resolution model with different higher-order inference methods.
End-to-End Coreference Resolution with Different Higher-Order Inference Methods This repository contains the implementation of the paper: Revealing th
A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm
Multi-Agent-Deep-Deterministic-Policy-Gradients A Pytorch implementation of the multi agent deep deterministic policy gradients(MADDPG) algorithm This
A Pythonic introduction to methods for scaling your data science and machine learning work to larger datasets and larger models, using the tools and APIs you know and love from the PyData stack (such as numpy, pandas, and scikit-learn).
This tutorial's purpose is to introduce Pythonistas to methods for scaling their data science and machine learning work to larger datasets and larger models, using the tools and APIs they know and love from the PyData stack (such as numpy, pandas, and scikit-learn).
The implementation of "Bootstrapping Semantic Segmentation with Regional Contrast".
ReCo - Regional Contrast This repository contains the source code of ReCo and baselines from the paper, Bootstrapping Semantic Segmentation with Regio
Proto-RL: Reinforcement Learning with Prototypical Representations
Proto-RL: Reinforcement Learning with Prototypical Representations This is a PyTorch implementation of Proto-RL from Reinforcement Learning with Proto
Using deep actor-critic model to learn best strategies in pair trading
Deep-Reinforcement-Learning-in-Stock-Trading Using deep actor-critic model to learn best strategies in pair trading Abstract Partially observed Markov
Use deep learning, genetic programming and other methods to predict stock and market movements
StockPredictions Use classic tricks, neural networks, deep learning, genetic programming and other methods to predict stock and market movements. Both
Scalable, event-driven, deep-learning-friendly backtesting library
...Minimizing the mean square error on future experience. - Richard S. Sutton BTGym Scalable event-driven RL-friendly backtesting library. Build on
Statistical package in Python based on Pandas
Pingouin is an open-source statistical package written in Python 3 and based mostly on Pandas and NumPy. Some of its main features are listed below. F
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilis
Sensitivity Analysis Library in Python (Numpy). Contains Sobol, Morris, Fractional Factorial and FAST methods.
Sensitivity Analysis Library (SALib) Python implementations of commonly used sensitivity analysis methods. Useful in systems modeling to calculate the
Probabilistic reasoning and statistical analysis in TensorFlow
TensorFlow Probability TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFl
High-performance TensorFlow library for quantitative finance.
TF Quant Finance: TensorFlow based Quant Finance Library Table of contents Introduction Installation TensorFlow training Development roadmap Examples
Text recognition (optical character recognition) with deep learning methods.
What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis | paper | training and evaluation data | failure cases and cle
A curated list of resources for text detection/recognition (optical character recognition ) with deep learning methods.
awesome-deep-text-detection-recognition A curated list of awesome deep learning based papers on text detection and recognition. Text Detection Papers
Multiple Pairwise Comparisons (Post Hoc) Tests in Python
scikit-posthocs is a Python package that provides post hoc tests for pairwise multiple comparisons that are usually performed in statistical data anal
SigOpt wrappers for scikit-learn methods
SigOpt + scikit-learn Interfacing This package implements useful interfaces and wrappers for using SigOpt and scikit-learn together Getting Started In
Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch
PyVarInf PyVarInf provides facilities to easily train your PyTorch neural network models using variational inference. Bayesian Deep Learning with Vari
ChainerRL is a deep reinforcement learning library built on top of Chainer.
ChainerRL ChainerRL is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Ch
Inspects Python source files and provides information about type and location of classes, methods etc
prospector About Prospector is a tool to analyse Python code and output information about errors, potential problems, convention violations and comple
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Bayesian Methods for Hackers Using Python and PyMC The Bayesian method is the natural approach to inference, yet it is hidden from readers behind chap
Inspects Python source files and provides information about type and location of classes, methods etc
prospector About Prospector is a tool to analyse Python code and output information about errors, potential problems, convention violations and comple