226 Repositories
Python kernel-methods Libraries
Rule Extraction Methods for Interactive eXplainability
REMIX: Rule Extraction Methods for Interactive eXplainability This repository contains a variety of tools and methods for extracting interpretable rul
This thesis is mainly concerned with state-space methods for a class of deep Gaussian process (DGP) regression problems
Doctoral dissertation of Zheng Zhao This thesis is mainly concerned with state-space methods for a class of deep Gaussian process (DGP) regression pro
A pure-python implementation of the UpSet suite of visualisation methods by Lex, Gehlenborg et al.
pyUpSet A pure-python implementation of the UpSet suite of visualisation methods by Lex, Gehlenborg et al. Contents Purpose How to install How it work
Current state of supervised and unsupervised depth completion methods
Awesome Depth Completion Table of Contents About Sparse-to-Dense Depth Completion Current State of Depth Completion Unsupervised VOID Benchmark Superv
A Python 3 package for state-of-the-art statistical dimension reduction methods
direpack: a Python 3 library for state-of-the-art statistical dimension reduction techniques This package delivers a scikit-learn compatible Python 3
Python package for missing-data imputation with deep learning
MIDASpy Overview MIDASpy is a Python package for multiply imputing missing data using deep learning methods. The MIDASpy algorithm offers significant
Lightweight and Modern kernel for VK Bots
This is the kernel for creating VK Bots written in Python 3.9
zeus is a Python implementation of the Ensemble Slice Sampling method.
zeus is a Python implementation of the Ensemble Slice Sampling method. Fast & Robust Bayesian Inference, Efficient Markov Chain Monte Carlo (MCMC), Bl
A number of methods in order to perform Natural Language Processing on live data derived from Twitter
A number of methods in order to perform Natural Language Processing on live data derived from Twitter
Learning kernels to maximize the power of MMD tests
Code for the paper "Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy" (arXiv:1611.04488; published at ICLR 2017), by Douga
Deep metric learning methods implemented in Chainer
Deep Metric Learning Implementation of several methods for deep metric learning in Chainer v4.2.0. Proxy-NCA: No Fuss Distance Metric Learning using P
Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.
Non-Metric Space Library (NMSLIB) Important Notes NMSLIB is generic but fast, see the results of ANN benchmarks. A standalone implementation of our fa
t-SNE and hierarchical clustering are popular methods of exploratory data analysis, particularly in biology.
tree-SNE t-SNE and hierarchical clustering are popular methods of exploratory data analysis, particularly in biology. Building on recent advances in s
Using some basic methods to show linkages and transformations of robotic arms
roboticArmVisualizer Python GUI application to create custom linkages and adjust joint angles. In the future, I plan to add 2d inverse kinematics solv
Pyfunctools is a module that provides functions, methods and classes that help in the creation of projects in python
Pyfunctools Pyfunctools is a module that provides functions, methods and classes that help in the creation of projects in python, bringing functional
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
ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels
ROCKET + MINIROCKET ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels. Data Mining and Knowledge D
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.
Data and code for the paper "Importance of Kernel Bandwidth in Quantum Machine Learning"
Reproducibility materials for "Importance of Kernel Bandwidth in Quantum Machine Learning" Repo structure: code contains Python scripts used to genera
Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernel
Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernel This repository is the official PyTorch implementation of BSRDM w
[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,
Code for our EMNLP 2021 paper "Learning Kernel-Smoothed Machine Translation with Retrieved Examples"
KSTER Code for our EMNLP 2021 paper "Learning Kernel-Smoothed Machine Translation with Retrieved Examples" [paper]. Usage Download the processed datas
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
Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-wise Distributed Data based on Pytorch Framework
VFedPCA+VFedAKPCA This is the official source code for the Paper: Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-
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
Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr\"om Method (NeurIPS 2021)
Skyformer This repository is the official implementation of Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr"om Method (NeurIPS 2021).
Public implementation of the Convolutional Motif Kernel Network (CMKN) architecture
CMKN Implementation of the convolutional motif kernel network (CMKN) introduced in Ditz et al., "Convolutional Motif Kernel Network", 2021. Testing Yo
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
Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr\"om Method (NeurIPS 2021)
Skyformer This repository is the official implementation of Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr"om Method (NeurIPS 2021).
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
GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily
GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily Abstract Graph Neural Networks (GNNs) are widely used on a
Simple tool, to update linux kernel on ubuntu
Kerbswap Simple tool, to update linux kernel on ubuntu Information At the moment, this tool only supports "Ubuntu" distributions, but will be expanded
[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
Driver Buddy Reloaded is an IDA Pro Python plugin that helps automate some tedious Windows Kernel Drivers reverse engineering tasks.
Driver Buddy Reloaded Quickstart Table of Contents Installation Usage About Driver Buddy Reloaded Finding DispatchDeviceControl Labelling WDM & WDF St
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
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
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
cairo_kernel is a simple Jupyter kernel for Cairo a smart contract programing language for STARKs.
cairo_kernel cairo_kernel is a simple Jupyter kernel for Cairo a smart contract programing language for STARKs. Installation Install virtualenv virtua
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
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes This repository contains the source code accompanying the paper: FlexConv: C
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
Inferred Model-based Fuzzer
IMF: Inferred Model-based Fuzzer IMF is a kernel API fuzzer that leverages an automated API model inferrence techinque proposed in our paper at CCS. I
Fuzzer for Linux Kernel Drivers
difuze: Fuzzer for Linux Kernel Drivers This repo contains all the sources (including setup scripts), you need to get difuze up and running. Tested on
Code for the USENIX 2017 paper: kAFL: Hardware-Assisted Feedback Fuzzing for OS Kernels
kAFL: Hardware-Assisted Feedback Fuzzing for OS Kernels Blazing fast x86-64 VM kernel fuzzing framework with performant VM reloads for Linux, MacOS an
Repo for FUZE project. I will also publish some Linux kernel LPE exploits for various real world kernel vulnerabilities here. the samples are uploaded for education purposes for red and blue teams.
Linux_kernel_exploits Some Linux kernel exploits for various real world kernel vulnerabilities here. More exploits are yet to come. This repo contains
A Kernel fuzzer focusing on race bugs
Razzer: Finding kernel race bugs through fuzzing Environment setup $ source scripts/envsetup.sh scripts/envsetup.sh sets up necessary environment var
Fuzzing the Kernel Using Unicornafl and AFL++
Unicorefuzz Fuzzing the Kernel using UnicornAFL and AFL++. For details, skim through the WOOT paper or watch this talk at CCCamp19. Is it any good? ye
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
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
The code for the NSDI'21 paper "BMC: Accelerating Memcached using Safe In-kernel Caching and Pre-stack Processing".
BMC The code for the NSDI'21 paper "BMC: Accelerating Memcached using Safe In-kernel Caching and Pre-stack Processing". BibTex entry available here. B
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.
Keval allows you to call arbitrary Windows kernel-mode functions from user mode, even (and primarily) on another machine.
Keval Keval allows you to call arbitrary Windows kernel-mode functions from user mode, even (and primarily) on another machine. The user mode portion
[ICCV 2021] Official Tensorflow Implementation for "Single Image Defocus Deblurring Using Kernel-Sharing Parallel Atrous Convolutions"
KPAC: Kernel-Sharing Parallel Atrous Convolutional block This repository contains the official Tensorflow implementation of the following paper: Singl
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.
Demonstrates how to divide a DL model into multiple IR model files (division) and introduce a simplest way to implement a custom layer works with OpenVINO IR models.
Demonstration of OpenVINO techniques - Model-division and a simplest-way to support custom layers Description: Model Optimizer in Intel(r) OpenVINO(tm
Official PyTorch code for Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution (MANet, ICCV2021)
Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution (MANet, ICCV2021) This repository is the official PyTorc
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
A curated list of resources for Image and Video Deblurring
A curated list of resources for Image and Video Deblurring
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
tinykernel - A minimal Python kernel so you can run Python in your Python
tinykernel - A minimal Python kernel so you can run Python in your Python
Exploring Image Deblurring via Blur Kernel Space (CVPR'21)
Exploring Image Deblurring via Encoded Blur Kernel Space About the project We introduce a method to encode the blur operators of an arbitrary dataset
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.
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
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
Official PyTorch code for CVPR 2020 paper "Deep Active Learning for Biased Datasets via Fisher Kernel Self-Supervision"
Deep Active Learning for Biased Datasets via Fisher Kernel Self-Supervision https://arxiv.org/abs/2003.00393 Abstract Active learning (AL) aims to min
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
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