62 Repositories
Python filtering Libraries
Tuple-sum-filter - Library to play with filtering numeric sequences by sums of their pairs, triplets, etc. With a bonus CLI demo
Tuple Sum Filter A library to play with filtering numeric sequences by sums of t
Negative Interactions for Improved Collaborative Filtering:
Negative Interactions for Improved Collaborative Filtering: Don’t go Deeper, go Higher This notebook provides an implementation in Python 3 of the alg
Filtering variational quantum algorithms for combinatorial optimization
Current gate-based quantum computers have the potential to provide a computational advantage if algorithms use quantum hardware efficiently.
Media Cloud Outlet Filtering
Using ABYZ and Media-Bias Fact-Check outlet databases, I've provided outlet CSV files for both and scripts to intended to match Media Cloud files to respective outlets.
GAN-based Matrix Factorization for Recommender Systems
GAN-based Matrix Factorization for Recommender Systems This repository contains the datasets' splits, the source code of the experiments and their res
Two types of Recommender System : Content-based Recommender System and Colaborating filtering based recommender system
Recommender-Systems Two types of Recommender System : Content-based Recommender System and Colaborating filtering based recommender system So the data
Consensus Learning from Heterogeneous Objectives for One-Class Collaborative Filtering
Consensus Learning from Heterogeneous Objectives for One-Class Collaborative Filtering This repository provides the source code of "Consensus Learning
(3DV 2021 Oral) Filtering by Cluster Consistency for Large-Scale Multi-Image Matching
Scalable Cluster-Consistency Statistics for Robust Multi-Object Matching (3DV 2021 Oral Presentation) Filtering by Cluster Consistency (FCC) is a very
[ WSDM '22 ] On Sampling Collaborative Filtering Datasets
On Sampling Collaborative Filtering Datasets This repository contains the implementation of many popular sampling strategies, along with various expli
🧮 Matrix Factorization for Collaborative Filtering is just Solving an Adjoint Latent Dirichlet Allocation Model after All
Accompanying source code to the paper "Matrix Factorization for Collaborative Filtering is just Solving an Adjoint Latent Dirichlet Allocation Model A
An Evaluation of Generative Adversarial Networks for Collaborative Filtering.
An Evaluation of Generative Adversarial Networks for Collaborative Filtering. This repository was developed by Fernando B. Pérez Maurera. Fernando is
YT-Spammer-Purge - Allows you easily scan for and delete scam comments using several methods
YouTube Spammer Purge What Is This? - Allows you to filter and search for spamme
Python bindings for FFmpeg - with complex filtering support
ffmpeg-python: Python bindings for FFmpeg Overview There are tons of Python FFmpeg wrappers out there but they seem to lack complex filter support. ff
Book Item Based Collaborative Filtering
Book-Item-Based-Collaborative-Filtering Collaborative filtering methods are used
Web interface for browsing, search and filtering recent arxiv submissions
Web interface for browsing, search and filtering recent arxiv submissions
Recommendationsystem - Movie-recommendation - matrixfactorization colloborative filtering recommendation system user
recommendationsystem matrixfactorization colloborative filtering recommendation
Autonomous Robots Kalman Filters
Autonomous Robots Kalman Filters The Kalman Filter is an easy topic. However, ma
Implementation for "Domain-Specific Bias Filtering for Single Labeled Domain Generalization"
DSBF Introduction This repository contains the implementation code for paper: Domain-Specific Bias Filtering for Single Labeled Domain Generalization
This project consists of a collaborative filtering algorithm to predict movie reviews ratings from a dataset of Netflix ratings.
Collaborative Filtering - Netflix movie reviews Description This project consists of a collaborative filtering algorithm to predict movie reviews rati
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing
Introduction Funnel-Transformer is a new self-attention model that gradually compresses the sequence of hidden states to a shorter one and hence reduc
SimpleITK is an image analysis toolkit with a large number of components supporting general filtering operations, image segmentation and registration
SimpleITK is an image analysis toolkit with a large number of components supporting general filtering operations, image segmentation and registration
📖 Deep Attentional Guided Image Filtering
📖 Deep Attentional Guided Image Filtering [Paper] Zhiwei Zhong, Xianming Liu, Junjun Jiang, Debin Zhao ,Xiangyang Ji Harbin Institute of Technology,
This repository contains the official MATLAB implementation of the TDA method for reverse image filtering
ReverseFilter TDA This repository contains the official MATLAB implementation of the TDA method for reverse image filtering proposed in the paper: "Re
Information Gain Filtration (IGF) is a method for filtering domain-specific data during language model finetuning. IGF shows significant improvements over baseline fine-tuning without data filtration.
Information Gain Filtration Information Gain Filtration (IGF) is a method for filtering domain-specific data during language model finetuning. IGF sho
Fast mesh denoising with data driven normal filtering using deep variational autoencoders
Fast mesh denoising with data driven normal filtering using deep variational autoencoders This is an implementation for the paper entitled "Fast mesh
An interactive grid for sorting, filtering, and editing DataFrames in Jupyter notebooks
qgrid Qgrid is a Jupyter notebook widget which uses SlickGrid to render pandas DataFrames within a Jupyter notebook. This allows you to explore your D
eBay's TSV Utilities: Command line tools for large, tabular data files. Filtering, statistics, sampling, joins and more.
Command line utilities for tabular data files This is a set of command line utilities for manipulating large tabular data files. Files of numeric and
R interface to fast.ai
R interface to fastai The fastai package provides R wrappers to fastai. The fastai library simplifies training fast and accurate neural nets using mod
Real-time ground filtering algorithm of cloud points acquired using Terrestrial Laser Scanner (TLS)
This repository contains tools to simulate the ground filtering process of a registered point cloud. The repository contains two filtering methods. The first method uses a normal vector, and fit to plane. The second method utilizes voxel adjacency, and fit to plane.
Extracting and filtering paraphrases by bridging natural language inference and paraphrasing
nli2paraphrases Source code repository accompanying the preprint Extracting and filtering paraphrases by bridging natural language inference and parap
HMLET (Hybrid-Method-of-Linear-and-non-linEar-collaborative-filTering-method)
Methods HMLET (Hybrid-Method-of-Linear-and-non-linEar-collaborative-filTering-method) Dynamically selecting the best propagation method for each node
Filtering user-generated video content(SberZvukTechDays)Filtering user-generated video content(SberZvukTechDays)
Filtering user-generated video content(SberZvukTechDays) Table of contents General info Team members Technologies Setup Result General info This is a
Unofficial pytorch implementation of the paper "Dynamic High-Pass Filtering and Multi-Spectral Attention for Image Super-Resolution"
DFSA Unofficial pytorch implementation of the ICCV 2021 paper "Dynamic High-Pass Filtering and Multi-Spectral Attention for Image Super-Resolution" (p
Code for our paper: Online Variational Filtering and Parameter Learning
Variational Filtering To run phi learning on linear gaussian (Fig1a) python linear_gaussian_phi_learning.py To run phi and theta learning on linear g
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
Graph ConvNets in PyTorch October 15, 2017 Xavier Bresson http://www.ntu.edu.sg/home/xbresson https://github.com/xbresson https://twitter.com/xbresson
YouTube Spam Detection with python
YouTube Spam Detection This code deletes spam comment on youtube videos based on two characteristics (currently) If the author of the comment has a se
Python Implementation of algorithms in Graph Mining, e.g., Recommendation, Collaborative Filtering, Community Detection, Spectral Clustering, Modularity Maximization, co-authorship networks.
Graph Mining Author: Jiayi Chen Time: April 2021 Implemented Algorithms: Network: Scrabing Data, Network Construbtion and Network Measurement (e.g., P
Learning Fair Representations for Recommendation: A Graph-based Perspective, WWW2021
FairGo WWW2021 Learning Fair Representations for Recommendation: A Graph-based Perspective As a key application of artificial intelligence, recommende
This is our implementation of GHCF: Graph Heterogeneous Collaborative Filtering (AAAI 2021)
GHCF This is our implementation of the paper: Chong Chen, Weizhi Ma, Min Zhang, Zhaowei Wang, Xiuqiang He, Chenyang Wang, Yiqun Liu and Shaoping Ma. 2
Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks
Bi-TGCF Tensorflow Implementation of BiTGCF: Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks. in CIKM20
Noise supression using deep filtering
DeepFilterNet A Low Complexity Speech Enhancement Framework for Full-Band Audio (48kHz) based on Deep Filtering. libDF contains Rust code used for dat
A Low Complexity Speech Enhancement Framework for Full-Band Audio (48kHz) based on Deep Filtering.
DeepFilterNet A Low Complexity Speech Enhancement Framework for Full-Band Audio (48kHz) based on Deep Filtering. libDF contains Rust code used for dat
MaRS - a recursive filtering framework that allows for truly modular multi-sensor integration
The Modular and Robust State-Estimation Framework, or short, MaRS, is a recursive filtering framework that allows for truly modular multi-sensor integration
This python module is an easy-to-use port of the text normalization used in the paper "Not low-resource anymore: Aligner ensembling, batch filtering, and new datasets for Bengali-English machine translation". It is intended to be used for normalizing / cleaning Bengali and English text.
normalizer This python module is an easy-to-use port of the text normalization used in the paper "Not low-resource anymore: Aligner ensembling, batch
The implement of papar "Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization"
SIGIR2021-EGLN The implement of paper "Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization" Neural graph based Col
LT-OCF: Learnable-Time ODE-based Collaborative Filtering, CIKM'21
LT-OCF: Learnable-Time ODE-based Collaborative Filtering Our proposed LT-OCF Our proposed dual co-evolving ODE Setup Python environment for LT-OCF Ins
PyTorch implementation of the wavelet analysis from Torrence & Compo
Continuous Wavelet Transforms in PyTorch This is a PyTorch implementation for the wavelet analysis outlined in Torrence and Compo (BAMS, 1998). The co
PyTorch implementations of Top-N recommendation, collaborative filtering recommenders.
PyTorch implementations of Top-N recommendation, collaborative filtering recommenders.
ML-powered Loan-Marketer Customer Filtering Engine
In Loan-Marketing business employees are required to call the user's to buy loans of several fields and in several magnitudes. If employees are calling everybody in the network it is also very lengthy and uncertain that most of the customers will buy it. So, there is a very need for a filtering system that segregates the customers who are unlikely to buy loans and the opposite. Loan-Web is visualized and made up on that context.
Elliot is a comprehensive recommendation framework that analyzes the recommendation problem from the researcher's perspective.
Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
Lightweight library for providing filtering mechanism for your APIs using SQLAlchemy
sqlalchemy-filters-plus is a light-weight extendable library for filtering queries with sqlalchemy. Install pip install sqlalchemy-fitlers-plus Usage
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.
FilterPy - Kalman filters and other optimal and non-optimal estimation filters in Python. NOTE: Imminent drop of support of Python 2.7, 3.4. See secti
Implementation of Kalman Filter in Python
Kalman Filter in Python This is a basic example of how Kalman filter works in Python. I do plan on refactoring and expanding this repo in the future.
This is a new web-based photo management application. Run it on your home server and it will let you find the right photo from your collection on any device. Smart filtering is made possible by object recognition, location awareness, color analysis and other ML algorithms.
Photonix Photo Manager This is a photo management application based on web technologies. Run it on your home server and it will let you find what you
Pyroomacoustics is a package for audio signal processing for indoor applications. It was developed as a fast prototyping platform for beamforming algorithms in indoor scenarios.
Summary Pyroomacoustics is a software package aimed at the rapid development and testing of audio array processing algorithms. The content of the pack
Python library for handling audio datasets.
AUDIOMATE Audiomate is a library for easy access to audio datasets. It provides the datastructures for accessing/loading different datasets in a gener
A generic system for filtering Django QuerySets based on user selections
Django Filter Django-filter is a reusable Django application allowing users to declaratively add dynamic QuerySet filtering from URL parameters. Full
Fast Python Collaborative Filtering for Implicit Feedback Datasets
Implicit Fast Python Collaborative Filtering for Implicit Datasets. This project provides fast Python implementations of several different popular rec
Spam filtering made easy for you
spammy Author: Tasdik Rahman Latest version: 1.0.3 Contents 1 Overview 2 Features 3 Example 3.1 Accuracy of the classifier 4 Installation 4.1 Upgradin
A Comparative Framework for Multimodal Recommender Systems
Cornac Cornac is a comparative framework for multimodal recommender systems. It focuses on making it convenient to work with models leveraging auxilia
Crab is a flexible, fast recommender engine for Python that integrates classic information filtering recommendation algorithms in the world of scientific Python packages (numpy, scipy, matplotlib).
Crab - A Recommendation Engine library for Python Crab is a flexible, fast recommender engine for Python that integrates classic information filtering r
adds flavor of interactive filtering to the traditional pipe concept of UNIX shell
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