Python Kernel-pca Resources

Eigenlearning This repo contains code for replicating the experiments of the paper A Theory of the Inductive Bias and Generalization of Kernel Regress

[CVPR 2022] Eigenlanes: Data-Driven Lane Descriptors for Structurally Diverse Lanes Dongkwon Jin, Wonhui Park, Seong-Gyun Jeong, Heeyeon Kwon, and Cha

This repository provides a library for efficient training of masked language models (MLM), built with fairseq. We fork fairseq to give researchers mor

Unfolded Deep Kernel Estimation for Blind Image Super-resolution Hongyi Zheng, Hongwei Yong, Lei Zhang, "Unfolded Deep Kernel Estimation for Blind Ima

Ookla Server KDE Plotting This notebook was created to map Ookla server locations as a Kernel Density Estimation (KDE) geographic map plot. Currently,

RE results graph visualization and company clustering Installation pip install -r requirements.txt python -m nltk.downloader stopwords python3.7 main.

Crypto Portfolio Clustering Crypto Portfolio Clustering with and without optimization techniques (elbow method, PCA). Analysis This is an anlysis of c

Nowadays we don't have time to listen to each and every song that we come across in a playlist. so, this project helps you. we used Spotify API for collecting the dataset information and able to do EDA and used K- means clustering technique and created new playlists in Spotify again.

Description This program presents convolutional kernel density estimation, a method used to detect intercritical epilpetic spikes (IEDs) in [Gardy et

PCAfold is an open-source Python library for generating, analyzing and improving low-dimensional manifolds obtained via Principal Component Analysis (PCA).

Slack IPython bot 🤯 One Slack bot to rule them all. PyBot. Just send Python code as a message. Install pip install slack-ipython To start the bot, si

On the adaptation of recurrent neural networks for system identification This repository contains the Python code to reproduce the results of the pape

PCA for dimensionality reduction combined with Kmeans Goal The Goal of this notebook is to apply a dimensionality reduction on a big dataset in order

pythonOS An operating system kernel made in python and assembly Wait what? It us

CVE-2022-21907 - Double Free in http.sys driver Summary An unauthenticated attacker can send an HTTP request with an "Accept-Encoding" HTTP request he

Time-aware Large Kernel (TaLK) Convolutions (Lioutas et al., 2020) This repository contains the source code, pre-trained models, as well as instructio

IHaskell You can now try IHaskell directly in your browser at CoCalc or mybinder.org. Alternatively, watch a talk and demo showing off IHaskell featur

ppReader-Kernel Intro Core identification module of AI powerful point reading system platform. Usage 硬件： Windows10、GPU：nvdia GTX 1060 、普通RBG相机 软件： con

Overview This Python package provides implementations of Augmented Principal Component Analysis (AugmentedPCA) - a family of linear factor models that

Linear (Un)supervised Image-to-Image Translation Examples for linear orthogonal transformations in PCA domain, learned without pairing supervision. Tr

A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers

Mini bioinformatics project: PCA on genotypes This repo contains the code from t

Semi-supervised Deep Kernel Learning This is the code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data

Channel Kernel Tracker is the channel where the bot will be sending the updates in. Introduction This is a Telegram Bot to Track Kernel Upstreams kern

pythonOS An operating system kernel made in python and assembly Wait what? It uses a custom compiler called snek that implements a part of python3.9 (

Poetry Kernel Use per-directory Poetry environments to run Jupyter kernels. No need to install a Jupyter kernel per Python virtual environment! The id

UX Analytics & A/B Testing

nettrace nettrace is is a powerful tool to trace network packet and diagnose network problem inside kernel on TencentOS. It make use of eBPF and BCC.

fastshap: A fast, approximate shap kernel fastshap was designed to be: Fast Calculating shap values can take an extremely long time. fastshap utilizes

xMCA | Maximum Covariance Analysis in Python The aim of this package is to provide a flexible tool for the climate science community to perform Maximu

AKGNN The source code for Adaptive Kernel Graph Neural Network at AAAI2022. Please cite our paper if you think our work is helpful to you: @inproceedi

jupyterlite-echo-kernel An echo kernel for JupyterLite. Requirements JupyterLite = 0.1.0a10 Install To install the extension, execute: pip install ju

About This is an IDA Pro (Interactive Disassembler) plugin allowing to automatically analyze and annotate Linux kernel alternatives (content of .altin

Self-Supervised Learning with Kernel Dependence Maximization This is the code for SSL-HSIC, a self-supervised learning loss proposed in the paper Self

KernelFunctionalOptimisation Code base for NeurIPS 2021 publication titled Kernel Functional Optimisation (KFO) We have conducted all our experiments

Cyclic 's Kernel ---- A iot Bike sytem based on RaspberryPi, Ardiuino, etc 0x1 What is This? Cyclic 's Kernel is an independent System With self-produ

#backdoor-HSIC (bd_HSIC) Accompanying code for the paper "A Kernel Test for Causal Association via Noise Contrastive Backdoor Adjustment". To generate

Created by Hugues THOMAS Introduction Update 27/04/2020: New PyTorch implementation available. With SemanticKitti, and Windows supported. This reposit

Cross-View Kernel Similarity Metric Learning Using Pairwise Constraints for Person Re-identification T M Feroz Ali, Subhasis Chaudhuri, ICVGIP-20-21

KML: A Machine Learning Framework for Operating Systems & Storage Systems Storage systems and their OS components are designed to accommodate a wide v

Prince is a library for doing factor analysis. This includes a variety of methods including principal component analysis (PCA) and correspondence anal

This is the kernel for creating VK Bots written in Python 3.9

Code for the paper "Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy" (arXiv:1611.04488; published at ICLR 2017), by Douga

ROCKET + MINIROCKET ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels. Data Mining and Knowledge D

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 This repository is the official PyTorch implementation of BSRDM w

KSTER Code for our EMNLP 2021 paper "Learning Kernel-Smoothed Machine Translation with Retrieved Examples" [paper]. Usage Download the processed datas

Nirs-Pls-Corn This code is a near-infrared spectrum modeling method based on PCA and pls 近红外光谱分析技术属于交叉领域，需要化学、计算机科学、生物科学等多领域的合作。为此，在（北邮邮电大学杨辉华老师团队）指导下

VFedPCA+VFedAKPCA This is the official source code for the Paper: Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-

Principal Component Analysis Principal Component Analysis (PCA) is a dimension-reduction algorithm. The idea is to use the singular value decompositio

Skyformer This repository is the official implementation of Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr"om Method (NeurIPS 2021).

CMKN Implementation of the convolutional motif kernel network (CMKN) introduced in Ditz et al., "Convolutional Motif Kernel Network", 2021. Testing Yo

Skyformer This repository is the official implementation of Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr"om Method (NeurIPS 2021).

GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily Abstract Graph Neural Networks (GNNs) are widely used on a

Kerbswap Simple tool, to update linux kernel on ubuntu Information At the moment, this tool only supports "Ubuntu" distributions, but will be expanded

Driver Buddy Reloaded Quickstart Table of Contents Installation Usage About Driver Buddy Reloaded Finding DispatchDeviceControl Labelling WDM & WDF St

cairo_kernel cairo_kernel is a simple Jupyter kernel for Cairo a smart contract programing language for STARKs. Installation Install virtualenv virtua

FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes This repository contains the source code accompanying the paper: FlexConv: C

ARES This repository contains the code for ARES (Adversarial Robustness Evaluation for Safety), a Python library for adversarial machine learning rese

popPhyl_PCA Performs PCA of genotypes. Works in two steps. 1. Input file A single fasta file containing different loci, in different populations/speci

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

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

kAFL: Hardware-Assisted Feedback Fuzzing for OS Kernels Blazing fast x86-64 VM kernel fuzzing framework with performant VM reloads for Linux, MacOS an

Linux_kernel_exploits Some Linux kernel exploits for various real world kernel vulnerabilities here. More exploits are yet to come. This repo contains

Razzer: Finding kernel race bugs through fuzzing Environment setup $ source scripts/envsetup.sh scripts/envsetup.sh sets up necessary environment var

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

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

Keval Keval allows you to call arbitrary Windows kernel-mode functions from user mode, even (and primarily) on another machine. The user mode portion

KPAC: Kernel-Sharing Parallel Atrous Convolutional block This repository contains the official Tensorflow implementation of the following paper: Singl

Demonstration of OpenVINO techniques - Model-division and a simplest-way to support custom layers Description: Model Optimizer in Intel(r) OpenVINO(tm

Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution (MANet, ICCV2021) This repository is the official PyTorc

A curated list of resources for Image and Video Deblurring

tinykernel - A minimal Python kernel so you can run Python in your Python

Exploring Image Deblurring via Encoded Blur Kernel Space About the project We introduce a method to encode the blur operators of an arbitrary dataset

Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

Deep Active Learning for Biased Datasets via Fisher Kernel Self-Supervision https://arxiv.org/abs/2003.00393 Abstract Active learning (AL) aims to min

Torchsort Fast, differentiable sorting and ranking in PyTorch. Pure PyTorch implementation of Fast Differentiable Sorting and Ranking (Blondel et al.)

30 Days Of Machine Learning Using Pytorch Objective of the repository is to learn and build machine learning models using Pytorch. List of Algorithms

PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds by Mutian Xu*, Runyu Ding*, Hengshuang Zhao, and Xiaojuan Qi. Int

Mesh Convolution This repository contains the implementation (in PyTorch) of the paper FULLY CONVOLUTIONAL MESH AUTOENCODER USING EFFICIENT SPATIALLY

[Due to the time taken @ uni, work + hell breaking loose in my life, since things have calmed down a bit, will continue commiting!!!] [By the way, I'm

MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification

Neural Tangents ICLR 2020 Video | Paper | Quickstart | Install guide | Reference docs | Release notes Overview Neural Tangents is a high-level neural

Animating the Optimization Trajectory of Neural Nets loss-landscape-anim lets you create animated optimization path in a 2D slice of the loss landscap

A Python interface to MVA SAS Overview This module creates a bridge between Python and SAS 9.4. This module enables a Python developer, familiar with

H2O H2O is an in-memory platform for distributed, scalable machine learning. H2O uses familiar interfaces like R, Python, Scala, Java, JSON and the Fl