Python Dialect-Classification Resources

About This repository provides data and code for the paper: Scalable Data Annotation Pipeline for High-Quality Large Speech Datasets Development (subm

Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning Overview This code is for paper: Not All Unlabeled Data are Equa

Pytorch-NLU，一个中文文本分类、序列标注工具包，支持中文长文本、短文本的多类、多标签分类任务，支持中文命名实体识别、词性标注、分词等序列标注任务。 Ptorch NLU, a Chinese text classification and sequence annotation toolkit, supports multi class and multi label classification tasks of Chinese long text and short text, and supports sequence annotation tasks such as Chinese named entity recognition, part of speech tagging and word segmentation.

This is a machine learning model deployment project of Iris classification model in a minimal UI using flask web framework and deployed it in Azure cloud using Azure app service. We initially made this project as a requirement for an internship at Indian Servers. We are now making it open to contribution.

Mail classification with tensorflow and MS Exchange Server (ham or spam).

🔥Deep Learning for 3D Point Clouds (IEEE TPAMI, 2020)

PaddlePaddle Vision Transformers State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 🤖 PaddlePaddle Visual Transformers (PaddleViT or

Channel LM Prompting (and beyond) This includes an original implementation of Sewon Min, Mike Lewis, Hannaneh Hajishirzi, Luke Zettlemoyer. "Noisy Cha

Relational Embedding for Few-Shot Classification (ICCV 2021) Dahyun Kang, Heeseung Kwon, Juhong Min, Minsu Cho [paper], [project hompage] We propose t

DSANet: Dynamic Segment Aggregation Network for Video-Level Representation Learning (ACMMM 2021) Overview We release the code of the DSANet (Dynamic S

DomainWordsDict, Chinese words dict that contains more than 68 domains, which can be used as text classification、knowledge enhance task。涵盖68个领域、共计916万词的专业词典知识库，可用于文本分类、知识增强、领域词汇库扩充等自然语言处理应用。

disclaimer: this code is modified from pytorch-tutorial Image classification with synthetic gradient in Pytorch I implement the Decoupled Neural Inter

Text Classification Baseline Pipeline for fast building text classification TF-IDF + LogReg baselines. Usage Instead of writing custom code for specif

Filtration Curves for Graph Representation This repository provides the code from the KDD'21 paper Filtration Curves for Graph Representation. Depende

Exploring Classification Equilibrium in Long-Tailed Object Detection (LOCE, ICCV 2021) Paper Introduction The conventional detectors tend to make imba

简介 通过PaddlePaddle框架复现了论文 Real-time Convolutional Neural Networks for Emotion and Gender Classification 中提出的两个模型，分别是SimpleCNN和MiniXception。利用 imdb_crop

Watermark-Robustness-Toolbox - Official PyTorch Implementation This repository contains the official PyTorch implementation of the following paper to

Audio Classification, Tagging & Sound Event Detection in PyTorch Progress: Fine-tune on audio classification Fine-tune on audio tagging Fine-tune on s

Detect the programming language of a source code

Framework overview This library allows to quickly implement different architectures based on Reservoir Computing (the family of approaches popularized

Torch-RGCN Torch-RGCN is a PyTorch implementation of the RGCN, originally proposed by Schlichtkrull et al. in Modeling Relational Data with Graph Conv

Parametric-Contrastive-Learning This repository contains the implementation code for ICCV2021 paper: Parametric Contrastive Learning (https://arxiv.or

High-Resolution Transformer for Dense Prediction Introduction This is the official implementation of High-Resolution Transformer (HRT). We present a H

Graph Convolutional Networks for Hyperspectral Image Classification Danfeng Hong, Lianru Gao, Jing Yao, Bing Zhang, Antonio Plaza, Jocelyn Chanussot T

The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification Code release for The Devil is in the Channels: Mutual-Channel

vanilla-rw-protonets-project Vanilla Prototypical Networks and PNs with Random Weights for image classification on Omniglot and mini-ImageNet. Made wi

This is official implementaion of paper "Token Shift Transformer for Video Classification". We achieve SOTA performance 80.40% on Kinetics-400 val. Paper link

Introdunction This is the official implementation of the paper "Query2Label: A Simple Transformer Way to Multi-Label Classification". Abstract This pa

Hierarchical Metadata-Aware Document Categorization under Weak Supervision This project provides a weakly supervised framework for hierarchical metada

FPGA & FreeNet Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification by Zhuo Zheng, Yanfei Zhong, Ailong M

TriageSQL The dataset and source code for our paper: "Did You Ask a Good Question? A Cross-Domain Question Intention Classification Benchmark for Text

FunMatch-Distillation TF2 implementation of knowledge distillation using the "function matching" hypothesis from the paper Knowledge distillation: A g

CrossFormer This repository is the code for our paper CrossFormer: A Versatile Vision Transformer Based on Cross-scale Attention. Introduction Existin

背景 安装教程 快速上手 （一）预训练模型 （二）机器翻译 （三）文本分类 TenTrans 进阶 1. 多语言机器翻译 2. 跨语言预训练 背景 TrenTrans是一个统一的端到端的多语言多任务预训练平台，支持多种预训练方式，以及序列生成和自然语言理解任务。 安装教程 git clone git

Active Learning allows you to efficiently label training data in a small-data scenario.

Random Erasing Data Augmentation =============================================================== black white random This code has the source code for

Structured Self-attentive sentence embeddings Implementation for the paper A Structured Self-Attentive Sentence Embedding, which was published in ICLR

Voice2Series-Reprogramming Voice2Series: Reprogramming Acoustic Models for Time Series Classification International Conference on Machine Learning (IC

This repo contains the official implementation of Spatial Contrastive Learning for Few-Shot Classification (SCL), which presents of a novel contrastive learning method applied to few-shot image classification in order to learn more general purpose embeddings, and facilitate the test-time adaptation to novel visual categories.

SGCN ⠀ A PyTorch implementation of Signed Graph Convolutional Network (ICDM 2018). Abstract Due to the fact much of today's data can be represented as

GAM ⠀⠀ A PyTorch implementation of Graph Classification Using Structural Attention (KDD 2018). Abstract Graph classification is a problem with practic

SimGNN ⠀⠀⠀ A PyTorch implementation of SimGNN: A Neural Network Approach to Fast Graph Similarity Computation (WSDM 2019). Abstract Graph similarity s

APPNP ⠀ A PyTorch implementation of Predict then Propagate: Graph Neural Networks meet Personalized PageRank (ICLR 2019). Abstract Neural message pass

CapsGNN ⠀⠀ A PyTorch implementation of Capsule Graph Neural Network (ICLR 2019). Abstract The high-quality node embeddings learned from the Graph Neur

SEAL ⠀⠀⠀ A PyTorch implementation of Semi-Supervised Graph Classification: A Hierarchical Graph Perspective (WWW 2019) Abstract Node classification an

ClusterGCN ⠀⠀ A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019). A

MaskFormer: Per-Pixel Classification is Not All You Need for Semantic Segmentation Bowen Cheng, Alexander G. Schwing, Alexander Kirillov [arXiv] [Proj

Multi-Temporal Scene Classification and Scene Change Detection with Correlation based Fusion Code for Multi-Temporal Scene Classification and Scene Ch

LM-MLC 一种基于完型填空的多标签分类算法 1 前言 本文主要介绍本人在全球人工智能技术创新大赛【赛道一】设计的一种基于完型填空(模板)的多标签分类算法：LM-MLC，该算法拟合能力很强能感知标签关联性，在多个数据集上测试表明该算法与主流算法无显著性差异，在该比赛数据集上的dev效果很好，但是由

Aspect-level Sentiment Classification Code and dataset for ACL2018 [paper] ‘‘Exploiting Document Knowledge for Aspect-level Sentiment Classification’’

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening Introduction This is an implementation of the model used for breast

Knodle (Knowledge-supervised Deep Learning Framework) - a new framework for weak supervision with neural networks. It provides a modularization for se

General Multi-label Image Classification with Transformers Jack Lanchantin, Tianlu Wang, Vicente Ordóñez Román, Yanjun Qi Conference on Computer Visio

The goal is to classify different birds species based on their songs/calls. Spectrograms have been extracted from the audio samples and used as features for classification.

Global Filter Networks for Image Classification Created by Yongming Rao, Wenliang Zhao, Zheng Zhu, Jiwen Lu, Jie Zhou This repository contains PyTorch

Data Efficient Stagewise Knowledge Distillation Table of Contents Data Efficient Stagewise Knowledge Distillation Table of Contents Requirements Image

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

Semantic Diversity Learning for Zero-Shot Multi-label Classification Paper Official PyTorch Implementation Avi Ben-Cohen, Nadav Zamir, Emanuel Ben Bar

DLCF-DCA codes for paper Combining Dynamic Local Context Focus and Dependency Cluster Attention for Aspect-level sentiment classification. submitted t

thai_sentiment The naive sentiment classification function based on NBSVM trained on wisesight_sentiment วิธีติดตั้ง pip install thai_sentiment==0.1.3

Random Walk Graph Neural Networks This repository is the official implementation of Random Walk Graph Neural Networks. Requirements Code is written in

Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline Ankit Goyal, Hei Law, Bowei Liu, Alejandro Newell, Jia Deng Internati

TunBERT is the first release of a pre-trained BERT model for the Tunisian dialect using a Tunisian Common-Crawl-based dataset. TunBERT was applied to three NLP downstream tasks: Sentiment Analysis (SA), Tunisian Dialect Identification (TDI) and Reading Comprehension Question-Answering (RCQA)

Patch-Rotation(PatchRot) Patch Rotation: A Self-Supervised Auxiliary Task for Robustness and Accuracy of Supervised Models Submitted to Neurips2021 To

[ICLR2021] CT-Net: Channel Tensorization Network for Video Classification @inproceedings{ li2021ctnet, title={{\{}CT{\}}-Net: Channel Tensorization Ne

PTR Code and datasets for our paper "PTR: Prompt Tuning with Rules for Text Classification" If you use the code, please cite the following paper: @art

kaggle-hpa-2021-7th-place-solution Code for 7th place solution of Human Protein Atlas - Single Cell Classification on Kaggle. A description of the met

Self-Classifier: Self-Supervised Classification Network Official PyTorch implementation and pretrained models of the paper Self-Supervised Classificat

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

Trajectory Embedding for Behavior Analysis (TREBA) Implementation from the paper: Jennifer J. Sun, Ann Kennedy, Eric Zhan, David J. Anderson, Yisong Y

Aerial Imagery dataset for fire detection: classification and segmentation using Unmanned Aerial Vehicle (UAV) Title FLAME (Fire Luminosity Airborne-b

gMLP PyTorch implementation of Pay Attention to MLPs. Quickstart Clone this repository. git clone https://github.com/jaketae/g-mlp.git Navigate to th

Adversarial Reciprocal Points Learning for Open Set Recognition Official PyTorch implementation of "Adversarial Reciprocal Points Learning for Open Se

DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification Created by Yongming Rao, Wenliang Zhao, Benlin Liu, Jiwen Lu, Jie Zhou, Ch

Delving into Deep Imbalanced Regression This repository contains the implementation code for paper: Delving into Deep Imbalanced Regression Yuzhe Yang

Quickly train T5 models in just 3 lines of code + ONNX support simpleT5 is built on top of PyTorch-lightning ⚡️ and Transformers 🤗 that lets you quic

SparseML is a toolkit that includes APIs, CLIs, scripts and libraries that apply state-of-the-art sparsification algorithms such as pruning and quantization to any neural network. General, recipe-driven approaches built around these algorithms enable the simplification of creating faster and smaller models for the ML performance community at large.

CrossViT : Cross-Attention Multi-Scale Vision Transformer for Image Classification This is an unofficial PyTorch implementation of CrossViT: Cross-Att

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

Introduction This is an official implementation of CvT: Introducing Convolutions to Vision Transformers. We present a new architecture, named Convolut

MLP-Mixer: An all-MLP Architecture for Vision This repo contains PyTorch implementation of MLP-Mixer: An all-MLP Architecture for Vision. Usage : impo

Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai

FNet: Mixing Tokens with Fourier Transforms Pytorch implementation of Fnet : Mixing Tokens with Fourier Transforms. Citation: @misc{leethorp2021fnet,

ResMLP - Pytorch Implementation of ResMLP, an all MLP solution to image classification out of Facebook AI, in Pytorch Install $ pip install res-mlp-py

Deep learning toolbox based on PyTorch for hyperspectral data classification.

mlp-mixer-tf Unofficial Implementation of MLP-Mixer [abs, pdf] in TensorFlow. Note: This project may have some bugs in it. I'm still learning how to i

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

** DEPRECATED ** This repo has been deprecated. Please visit Megatron-LM for our up to date Large-scale unsupervised pretraining and finetuning code.

SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge Introduction SentiLARE is a sentiment-aware pre-trained language

MixStyle This repo contains the code of our ICLR'21 paper, "Domain Generalization with MixStyle". The OpenReview link is https://openreview.net/forum?

Towards Good Practices for Efficiently Annotating Large-Scale Image Classification Datasets This is the official implementation of "Towards Good Pract

Implementation of different ML Algorithms from scratch, written in Python 3.x

TorchFlare TorchFlare is a simple, beginner-friendly and an easy-to-use PyTorch Framework train your models without much effort. It provides an almost

Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu,

CorNet Correlation Networks for Extreme Multi-label Text Classification Prerequisites python==3.6.3 pytorch==1.2.0 torchgpipe==0.0.5 click==7.0 ruamel

Human Attention for Text Classification Re-implementation of the paper Human Attention Maps for Text Classification: Do Humans and Neural Networks Foc

ImageNet-21K Pretraining for the Masses Paper | Pretrained models Official PyTorch Implementation Tal Ridnik, Emanuel Ben-Baruch, Asaf Noy, Lihi Zelni

Attack classification models with transferability, black-box attack; unrestricted adversarial attacks on imagenet, CVPR2021 安全AI挑战者计划第六期：ImageNet无限制对抗攻击 决赛第四名（team name: Advers）

Trove Trove is a research framework for building weakly supervised (bio)medical named entity recognition (NER) and other entity attribute classifiers

CeiT : Convolutional enhanced image Transformer This is an unofficial PyTorch implementation of Incorporating Convolution Designs into Visual Transfor