3742 Repositories
Python deep-sequential-model Libraries
Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity
[ICLR 2022] Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity by Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
Driver Analysis with Factors and Forests: An Automated Data Science Tool using Python
Driver Analysis with Factors and Forests: An Automated Data Science Tool using Python 📊
In this workshop we will be exploring NLP state of the art transformers, with SOTA models like T5 and BERT, then build a model using HugginFace transformers framework.
Transformers are all you need In this workshop we will be exploring NLP state of the art transformers, with SOTA models like T5 and BERT, then build a
The MLOps is the process of continuous integration and continuous delivery of Machine Learning artifacts as a software product, keeping it inside a loop of Design, Model Development and Operations.
MLOps The MLOps is the process of continuous integration and continuous delivery of Machine Learning artifacts as a software product, keeping it insid
This is the source code of the 1st place solution for segmentation task (with Dice 90.32%) in 2021 CCF BDCI challenge.
1st place solution in CCF BDCI 2021 ULSEG challenge This is the source code of the 1st place solution for ultrasound image angioma segmentation task (
Optical character recognition for Japanese text, with the main focus being Japanese manga
Manga OCR Optical character recognition for Japanese text, with the main focus being Japanese manga. It uses a custom end-to-end model built with Tran
DocEnTr: An end-to-end document image enhancement transformer
DocEnTR Description Pytorch implementation of the paper DocEnTr: An End-to-End Document Image Enhancement Transformer. This model is implemented on to
RuCLIP-SB (Russian Contrastive Language–Image Pretraining SWIN-BERT) is a multimodal model for obtaining images and text similarities and rearranging captions and pictures. Unlike other versions of the model we use BERT for text encoder and SWIN transformer for image encoder.
ruCLIP-SB RuCLIP-SB (Russian Contrastive Language–Image Pretraining SWIN-BERT) is a multimodal model for obtaining images and text similarities and re
Explaining Deep Neural Networks - A comparison of different CAM methods based on an insect data set
Explaining Deep Neural Networks - A comparison of different CAM methods based on an insect data set This is the repository for the Deep Learning proje
Computer Vision Paper Reviews with Key Summary of paper, End to End Code Practice and Jupyter Notebook converted papers
Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 The repository provides 100+ Pap
🤖 Project template for your next awesome AI project. 🦾
🤖 AI Awesome Project Template 👋 Template author You may want to adjust badge links in a README.md file. 💎 Installation with pip Installation is as
A large-scale benchmark for co-optimizing the design and control of soft robots, as seen in NeurIPS 2021.
Evolution Gym A large-scale benchmark for co-optimizing the design and control of soft robots. As seen in Evolution Gym: A Large-Scale Benchmark for E
Deep Inertial Prediction (DIPr)
Deep Inertial Prediction For more information and context related to this repo, please refer to our website. Getting Started (non Docker) Note: you wi
Deep ViT Features as Dense Visual Descriptors
dino-vit-features [paper] [project page] Official implementation of the paper "Deep ViT Features as Dense Visual Descriptors". We demonstrate the effe
This repository contains code accompanying the paper "An End-to-End Chinese Text Normalization Model based on Rule-Guided Flat-Lattice Transformer"
FlatTN This repository contains code accompanying the paper "An End-to-End Chinese Text Normalization Model based on Rule-Guided Flat-Lattice Transfor
SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking
SPLADE 🍴 + 🥄 = 🔎 This repository contains the weights for four models as well as the code for running inference for our two papers: [v1]: SPLADE: S
Hand gesture recognition model that can be used as a remote control for a smart tv.
Gesture_recognition The training data consists of a few hundred videos categorised into one of the five classes. Each video (typically 2-3 seconds lon
Heart Arrhythmia Classification
This program takes and input of an ECG in European Data Format (EDF) and outputs the classification for heartbeats into normal vs different types of arrhythmia . It uses a deep learning model for classification purposes.
NLP applications using deep learning.
NLP-Natural-Language-Processing NLP applications using deep learning like text generation etc. 1- Poetry Generation: Using a collection of Irish Poem
Multi-label classification of retinal disorders
Multi-label classification of retinal disorders This is a deep learning course project. The goal is to develop a solution, using computer vision techn
RobustVideoMatting and background composing in one model by using onnxruntime.
RVM_onnx_compose RobustVideoMatting and background composing in one model by using onnxruntime. Usage pip install -r requirements.txt python infer_cam
A model to classify a piece of news as REAL or FAKE
Fake_news_classification A model to classify a piece of news as REAL or FAKE. This python project of detecting fake news deals with fake and real news
MusicYOLO framework uses the object detection model, YOLOx, to locate notes in the spectrogram.
MusicYOLO MusicYOLO framework uses the object detection model, YOLOX, to locate notes in the spectrogram. Its performance on the ISMIR2014 dataset, MI
This repository contains the raw data and a python notebook to ingest historical A&E attendance data and then use a simple Prophet model to predict the number of A&E attendances in England if the COVID-19 pandemic had not happened
ae_attendances_modelling This repository contains the raw data and a python notebook to ingest historical A&E attendance data and then use a simple Pr
Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive losses
Self-supervised learning Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive loss
PyTorch framework, for reproducing experiments from the paper Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks
Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks. Code, based on the PyTorch framework, for reprodu
This repository serves as a place to document a toy attempt on how to create a generative text model in Catalan, based on GPT-2
GPT-2 Catalan playground and scripts to train a GPT-2 model either from scrath or from another pretrained model.
Annotate datasets with a semi-trained or fully trained YOLOv5 model
YOLOv5 Auto Annotator Annotate datasets with a semi-trained or fully trained YOLOv5 model Prerequisites Ubuntu =20.04 Python =3.7 System dependencie
NaturalCC is a sequence modeling toolkit that allows researchers and developers to train custom models
NaturalCC NaturalCC is a sequence modeling toolkit that allows researchers and developers to train custom models for many software engineering tasks,
WebUAV-3M: A Benchmark Unveiling the Power of Million-Scale Deep UAV Tracking
WebUAV-3M: A Benchmark Unveiling the Power of Million-Scale Deep UAV Tracking [Paper Link] Abstract In this work, we contribute a new million-scale Un
smc.covid is an R package related to the paper A sequential Monte Carlo approach to estimate a time varying reproduction number in infectious disease models: the COVID-19 case by Storvik et al
smc.covid smc.covid is an R package related to the paper A sequential Monte Carlo approach to estimate a time varying reproduction number in infectiou
Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22)
Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22) Ok-Topk is a scheme for distributed training with sparse gradients
High-fidelity 3D Model Compression based on Key Spheres
High-fidelity 3D Model Compression based on Key Spheres This repository contains the implementation of the paper: Yuanzhan Li, Yuqi Liu, Yujie Lu, Siy
Self-Supervised Deep Blind Video Super-Resolution
Self-Blind-VSR Paper | Discussion Self-Supervised Deep Blind Video Super-Resolution By Haoran Bai and Jinshan Pan Abstract Existing deep learning-base
This repository contains the implementation of the HealthGen model, a generative model to synthesize realistic EHR time series data with missingness
HealthGen: Conditional EHR Time Series Generation This repository contains the implementation of the HealthGen model, a generative model to synthesize
MetaTTE: a Meta-Learning Based Travel Time Estimation Model for Multi-city Scenarios
MetaTTE: a Meta-Learning Based Travel Time Estimation Model for Multi-city Scenarios This is the official TensorFlow implementation of MetaTTE in the
An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional Filters
CNN-Filter-DB An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional Filters Paul Gavrikov, Janis Keuper Paper: htt
OpenIPDM is a MATLAB open-source platform that stands for infrastructures probabilistic deterioration model
Open-Source Toolbox for Infrastructures Probabilistic Deterioration Modelling OpenIPDM is a MATLAB open-source platform that stands for infrastructure
HEAM: High-Efficiency Approximate Multiplier Optimization for Deep Neural Networks
Approximate Multiplier by HEAM What's HEAM? HEAM is a general optimization method to generate high-efficiency approximate multipliers for specific app
A deep learning framework for historical document image analysis
DIVA-DAF Description A deep learning framework for historical document image analysis. How to run Install dependencies # clone project git clone https
A PyTorch implementation for our paper "Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation".
Dual-Contrastive-Learning A PyTorch implementation for our paper "Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation". Y
Generate fine-tuning samples & Fine-tuning the model & Generate samples by transferring Note On
UPMT Generate fine-tuning samples & Fine-tuning the model & Generate samples by transferring Note On See main.py as an example: from model import PopM
On the adaptation of recurrent neural networks for system identification
On the adaptation of recurrent neural networks for system identification This repository contains the Python code to reproduce the results of the pape
Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial Network
Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial Network This is the official implementation of
Which Style Makes Me Attractive? Interpretable Control Discovery and Counterfactual Explanation on StyleGAN
Interpretable Control Exploration and Counterfactual Explanation (ICE) on StyleGAN Which Style Makes Me Attractive? Interpretable Control Discovery an
CvT2DistilGPT2 is an encoder-to-decoder model that was developed for chest X-ray report generation.
CvT2DistilGPT2 Improving Chest X-Ray Report Generation by Leveraging Warm-Starting This repository houses the implementation of CvT2DistilGPT2 from [1
Combinatorial model of ligand-receptor binding
Combinatorial model of ligand-receptor binding The binding of ligands to receptors is the starting point for many import signal pathways within a cell
Do Smart Glasses Dream of Sentimental Visions? Deep Emotionship Analysis for Eyewear Devices
EMOShip This repository contains the EMO-Film dataset described in the paper "Do Smart Glasses Dream of Sentimental Visions? Deep Emotionship Analysis
Pytorch implementation of the paper DocEnTr: An End-to-End Document Image Enhancement Transformer.
DocEnTR Description Pytorch implementation of the paper DocEnTr: An End-to-End Document Image Enhancement Transformer. This model is implemented on to
Ensemble Learning Priors Driven Deep Unfolding for Scalable Snapshot Compressive Imaging [PyTorch]
Ensemble Learning Priors Driven Deep Unfolding for Scalable Snapshot Compressive Imaging [PyTorch] Abstract Snapshot compressive imaging (SCI) can rec
Official code of Team Yao at Multi-Modal-Fact-Verification-2022
Official code of Team Yao at Multi-Modal-Fact-Verification-2022 A Multi-Modal Fact Verification dataset released as part of the De-Factify workshop in
Check out the StyleGAN repo and place it in the same directory hierarchy as the present repo
Variational Model Inversion Attacks Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti, Richard Zemel, Alireza Makhzani Most commands are in run_scripts. W
Model Agnostic Interpretability for Multiple Instance Learning
MIL Model Agnostic Interpretability This repo contains the code for "Model Agnostic Interpretability for Multiple Instance Learning". Overview Executa
Novel and high-performance medical image classification pipelines are heavily utilizing ensemble learning strategies
An Analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural Networks Novel and high-performance medical ima
Blind Video Temporal Consistency via Deep Video Prior
deep-video-prior (DVP) Code for NeurIPS 2020 paper: Blind Video Temporal Consistency via Deep Video Prior PyTorch implementation | paper | project web
Hyperparameters tuning and features selection are two common steps in every machine learning pipeline.
shap-hypetune A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models. Overview Hyperparameters t
Labelme is a graphical image annotation tool, It is written in Python and uses Qt for its graphical interface
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
A classification model capable of accurately predicting the price of secondhand cars
The purpose of this project is create a classification model capable of accurately predicting the price of secondhand cars. The data used for model building is open source and has been added to this repository. Most packages used are usually pre-installed in most developed environments and tools like collab, jupyter, etc. This can be useful for people looking to enhance the way the code their predicitve models and efficient ways to deal with tabular data!
Style transfer between images was performed using the VGG19 model
Style transfer between images was performed using the VGG19 model. The necessary codes, libraries and all other information of this project are available below
Audio Source Separation is the process of separating a mixture into isolated sounds from individual sources
Audio Source Separation is the process of separating a mixture into isolated sounds from individual sources (e.g. just the lead vocals).
Predict the spans of toxic posts that were responsible for the toxic label of the posts
toxic-spans-detection An attempt at the SemEval 2021 Task 5: Toxic Spans Detection. The Toxic Spans Detection task of SemEval2021 required participant
Melanoma Skin Cancer Detection using Convolutional Neural Networks and Transfer Learning🕵🏻♂️
This is a Kaggle competition in which we have to identify if the given lesion image is malignant or not for Melanoma which is a type of skin cancer.
EasyRequests is a minimalistic HTTP-Request Library that wraps aiohttp and asyncio in a small package that allows for sequential, parallel or even single requests
EasyRequests EasyRequests is a minimalistic HTTP-Request Library that wraps aiohttp and asyncio in a small package that allows for sequential, paralle
The Dual Memory is build from a simple CNN for the deep memory and Linear Regression fro the fast Memory
Simple-DMA a simple Dual Memory Architecture for classifications. based on the paper Dual-Memory Deep Learning Architectures for Lifelong Learning of
This library provides an abstraction to perform Model Versioning using Weight & Biases.
Description This library provides an abstraction to perform Model Versioning using Weight & Biases. Features Version a new trained model Promote a mod
Easy to use and customizable SOTA Semantic Segmentation models with abundant datasets in PyTorch
Semantic Segmentation Easy to use and customizable SOTA Semantic Segmentation models with abundant datasets in PyTorch Features Applicable to followin
A cut down version of QUANT containing just the model in Python (QUANTPy)
A cut down version of QUANT containing just the model in Python (QUANTPy)
SAS: Self-Augmentation Strategy for Language Model Pre-training
SAS: Self-Augmentation Strategy for Language Model Pre-training This repository
This repo provides the source code & data of our paper "GreaseLM: Graph REASoning Enhanced Language Models"
GreaseLM: Graph REASoning Enhanced Language Models This repo provides the source code & data of our paper "GreaseLM: Graph REASoning Enhanced Language
EdiBERT is a generative model based on a bi-directional transformer, suited for image manipulation
EdiBERT, a generative model for image editing EdiBERT is a generative model based on a bi-directional transformer, suited for image manipulation. The
Unsupervised Feature Loss (UFLoss) for High Fidelity Deep learning (DL)-based reconstruction
Unsupervised Feature Loss (UFLoss) for High Fidelity Deep learning (DL)-based reconstruction Official github repository for the paper High Fidelity De
AirPose: Multi-View Fusion Network for Aerial 3D Human Pose and Shape Estimation
AirPose AirPose: Multi-View Fusion Network for Aerial 3D Human Pose and Shape Estimation Check the teaser video This repository contains the code of A
A Confidence-based Iterative Solver of Depths and Surface Normals for Deep Multi-view Stereo
idn-solver Paper | Project Page This repository contains the code release of our ICCV 2021 paper: A Confidence-based Iterative Solver of Depths and Su
Neural Tangent Generalization Attacks (NTGA)
Neural Tangent Generalization Attacks (NTGA) ICML 2021 Video | Paper | Quickstart | Results | Unlearnable Datasets | Competitions | Citation Overview
On Out-of-distribution Detection with Energy-based Models
On Out-of-distribution Detection with Energy-based Models This repository contains the code for the experiments conducted in the paper On Out-of-distr
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models Abstract Many applications of generative models rely on the marginali
A hybrid framework (neural mass model + ML) for SC-to-FC prediction
The current workflow simulates brain functional connectivity (FC) from structural connectivity (SC) with a neural mass model. Gradient descent is applied to optimize the parameters in the neural mass model.
RoNER is a Named Entity Recognition model based on a pre-trained BERT transformer model trained on RONECv2
RoNER RoNER is a Named Entity Recognition model based on a pre-trained BERT transformer model trained on RONECv2. It is meant to be an easy to use, hi
Neuralnetwork - Basic Multilayer Perceptron Neural Network for deep learning
Neural Network Just a basic Neural Network module Usage Example Importing Module
This porject is intented to build the most accurate model for predicting the porbability of loan default
Estimating-Loan-Default-Probability IBA ML2 Mid-project / Kaggle Competition This porject is intented to build the most accurate model for predicting
This is a Deep Leaning API for classifying emotions from human face and human audios.
Emotion AI This is a Deep Leaning API for classifying emotions from human face and human audios. Starting the server To start the server first you nee
Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt)
Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt) Task Training huge unsupervised deep neural networks yields to strong progress in
Sdf sparse conv - Deep Learning on SDF for Classifying Brain Biomarkers
Deep Learning on SDF for Classifying Brain Biomarkers To reproduce the results f
DTCN IJCAI - Sequential prediction learning framework and algorithm
DTCN This is the implementation of our paper "Sequential Prediction of Social Me
Labelbox is the fastest way to annotate data to build and ship artificial intelligence applications
Labelbox Labelbox is the fastest way to annotate data to build and ship artificial intelligence applications. Use this github repository to help you s
CVAT is free, online, interactive video and image annotation tool for computer vision
Computer Vision Annotation Tool (CVAT) CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our
Toward Model Interpretability in Medical NLP
Toward Model Interpretability in Medical NLP LING380: Topics in Computational Linguistics Final Project James Cross ([email protected]) and Daniel Kim
Simple and understandable swin-transformer OCR project
swin-transformer-ocr ocr with swin-transformer Overview Simple and understandable swin-transformer OCR project. The model in this repository heavily r
A library for benchmarking, developing and deploying deep learning anomaly detection algorithms
A library for benchmarking, developing and deploying deep learning anomaly detection algorithms Key Features • Getting Started • Docs • License Introd
Awesome Transformers in Medical Imaging
This repo supplements our Survey on Transformers in Medical Imaging Fahad Shamshad, Salman Khan, Syed Waqas Zamir, Muhammad Haris Khan, Munawar Hayat,
List of awesome things around semantic segmentation 🎉
Awesome Semantic Segmentation List of awesome things around semantic segmentation 🎉 Semantic segmentation is a computer vision task in which we label
Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks
Introduction This repository contains the modified caffe library and network architectures for our paper "Automated Melanoma Recognition in Dermoscopy
Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images
Lung Segmentation (2D) Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images. Demo See the application of the
Pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments
Cascaded-FCN This repository contains the pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments the liver and its lesions out of
Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network
ild-cnn This is supplementary material for the manuscript: "Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neur
Deep Learning to Improve Breast Cancer Detection on Screening Mammography
Shield: This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Deep Learning to Improve Breast
Raster Vision is an open source Python framework for building computer vision models on satellite, aerial, and other large imagery sets
Raster Vision is an open source Python framework for building computer vision models on satellite, aerial, and other large imagery sets (including obl
This repository contains code, network definitions and pre-trained models for working on remote sensing images using deep learning
Deep learning for Earth Observation This repository contains code, network definitions and pre-trained models for working on remote sensing images usi
🛰️ Awesome Satellite Imagery Datasets
Awesome Satellite Imagery Datasets List of aerial and satellite imagery datasets with annotations for computer vision and deep learning. Newest datase