7236 Repositories
Python Training-a-deep-learning-model-on-the-noisy-CIFAR-dataset Libraries
Proyecto - Desgaste y rendimiento de empleados de IBM HR Analytics
Acceder al código desde Google Colab para poder ver de manera adecuada todas las visualizaciones y poder interactuar con ellas. Links de acceso: Noteb
This repository contains the re-implementation of our paper deSpeckNet: Generalizing Deep Learning Based SAR Image Despeckling
deSpeckNet-TF-GEE This repository contains the re-implementation of our paper deSpeckNet: Generalizing Deep Learning Based SAR Image Despeckling publi
The NEOSSat is a dual-mission microsatellite designed to detect potentially hazardous Earth-orbit-crossing asteroids and track objects that reside in deep space
The NEOSSat is a dual-mission microsatellite designed to detect potentially hazardous Earth-orbit-crossing asteroids and track objects that reside in deep space
Wordle Env: A Daily Word Environment for Reinforcement Learning
Wordle Env: A Daily Word Environment for Reinforcement Learning Setup Steps: git pull [email protected]:alex-nooj/wordle_env.git From the wordle_env dire
A modification of Daniel Russell's notebook merged with Katherine Crowson's hq-skip-net changes
Edits made to this repo by Katherine Crowson I have added several features to this repository for use in creating higher quality generative art (featu
CS550 Machine Learning course project on CNN Detection.
CNN Detection (CS550 Machine Learning Project) Team Members (Tensor) : Yadava Kishore Chodipilli (11940310) Thashmitha BS (11941250) This is a work do
Our product DrLeaf which not only makes the work easier but also reduces the effort and expenditure of the farmer to identify the disease and its treatment methods.
Our product DrLeaf which not only makes the work easier but also reduces the effort and expenditure of the farmer to identify the disease and its treatment methods. We have to upload the image of an affected plant’s leaf through our website and our plant disease prediction model predicts and returns the disease name. And along with the disease name, we also provide the best suitable methods to cure the disease.
Based on the given clinical dataset, Predict whether the patient having Heart Disease or Not having Heart Disease
Heart_Disease_Classification Based on the given clinical dataset, Predict whether the patient having Heart Disease or Not having Heart Disease Dataset
Learning -- Numpy January 2022 - winter'22
Numerical-Python Numpy NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along
Create a machine learning model which will predict if the mortgage will be approved or not based on 5 variables
Mortgage-Application-Analysis Create a machine learning model which will predict if the mortgage will be approved or not based on 5 variables: age, in
TorchGRL is the source code for our paper Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffic Environments for IV 2022.
TorchGRL TorchGRL is the source code for our paper Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffi
Multilingual finetuning of Machine Translation model on low-resource languages. Project for Deep Natural Language Processing course.
Low-resource-Machine-Translation This repository contains the code for the project relative to the course Deep Natural Language Processing. The goal o
To-Be is a machine learning challenge on CodaLab Platform about Mortality Prediction
To-Be is a machine learning challenge on CodaLab Platform about Mortality Prediction. The challenge aims to adress the problems of medical imbalanced data classification.
LSTM model - IMDB review sentiment analysis
NLP - Movie review sentiment analysis The colab notebook contains the code for building a LSTM Recurrent Neural Network that gives 87-88% accuracy on
Template repository for managing machine learning research projects built with PyTorch-Lightning
Tutorial Repository with a minimal example for showing how to deploy training across various compute infrastructure.
This is a working model for which I have used python.
Jarvis_voiceAssistance This is a working model for which I have used python. This model can: 1)Play a video or song on youtube. 2)Tell us time. 3)Tell
spaCy-wrap: For Wrapping fine-tuned transformers in spaCy pipelines
spaCy-wrap: For Wrapping fine-tuned transformers in spaCy pipelines spaCy-wrap is minimal library intended for wrapping fine-tuned transformers from t
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
Pytorch Implementation of Continual Learning With Filter Atom Swapping (ICLR'22 Spolight) Paper
Continual Learning With Filter Atom Swapping Pytorch Implementation of Continual Learning With Filter Atom Swapping (ICLR'22 Spolight) Paper If find t
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 📊
Codes and models for the paper "Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction".
GNN_PPI Codes and models for the paper "Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction". Lear
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
Repository for the Demo of using DVC with PyCaret & MLOps (DVC Office Hours - 20th Jan, 2022)
Using DVC with PyCaret & FastAPI (Demo) This repo contains all the resources for my demo explaining how to use DVC along with other interesting tools
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
My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs (GNN, GAT, GraphSAGE, GCN)
machine-learning-with-graphs My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs Course materials can be
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
Notebooks, slides and dataset of the CorrelAid Machine Learning Winter School
CorrelAid Machine Learning Winter School Welcome to the CorrelAid ML Winter School! Task The problem we want to solve is to classify trees in Roosevel
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
OpenAi's gym environment wrapper to vectorize them with Ray
Ray Vector Environment Wrapper You would like to use Ray to vectorize your environment but you don't want to use RLLib ? You came to the right place !
SNCSE: Contrastive Learning for Unsupervised Sentence Embedding with Soft Negative Samples
SNCSE SNCSE: Contrastive Learning for Unsupervised Sentence Embedding with Soft Negative Samples This is the repository for SNCSE. SNCSE aims to allev
🤖 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
Training DiffWave using variational method from Variational Diffusion Models.
Variational DiffWave Training DiffWave using variational method from Variational Diffusion Models. Quick Start python train_distributed.py discrete_10
RRL: Resnet as representation for Reinforcement Learning
Resnet as representation for Reinforcement Learning (RRL) is a simple yet effective approach for training behaviors directly from visual inputs. We demonstrate that features learned by standard image classification models are general towards different task, robust to visual distractors, and when used in conjunction with standard Imitation Learning or Reinforcement Learning pipelines can efficiently acquire behaviors directly from proprioceptive inputs.
Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
DART Implementation for ICLR2022 paper Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners. Environment [email protected] Use pi
This repository provides the official code for GeNER (an automated dataset Generation framework for NER).
GeNER This repository provides the official code for GeNER (an automated dataset Generation framework for NER). Overview of GeNER GeNER allows you to
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
TalkingHead-1KH is a talking-head dataset consisting of YouTube videos
TalkingHead-1KH Dataset TalkingHead-1KH is a talking-head dataset consisting of YouTube videos, originally created as a benchmark for face-vid2vid: On
BaseCls BaseCls 是一个基于 MegEngine 的预训练模型库,帮助大家挑选或训练出更适合自己科研或者业务的模型结构
BaseCls BaseCls 是一个基于 MegEngine 的预训练模型库,帮助大家挑选或训练出更适合自己科研或者业务的模型结构。 文档地址:https://basecls.readthedocs.io 安装 安装环境 BaseCls 需要 Python = 3.6。 BaseCls 依赖 M
TIANCHI Purchase Redemption Forecast Challenge
TIANCHI Purchase Redemption Forecast Challenge
Fundamentals of Machine Learning
Fundamentals-of-Machine-Learning This repository introduces the basics of machine learning algorithms for preprocessing, regression and classification
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
A face dataset generator with out-of-focus blur detection and dynamic interval adjustment.
A face dataset generator with out-of-focus blur detection and dynamic interval adjustment.
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
FedML: A Research Library and Benchmark for Federated Machine Learning
FedML: A Research Library and Benchmark for Federated Machine Learning 📄 https://arxiv.org/abs/2007.13518 News 2021-02-01 (Award): #NeurIPS 2020# Fed
Machine Learning e Data Science com Python
Machine Learning e Data Science com Python Arquivos do curso de Data Science e Machine Learning com Python na Udemy, cliqe aqui para acessá-lo. O prin
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
Painless Machine Learning for python based on scikit-learn
PlainML Painless Machine Learning Library for python based on scikit-learn. Install pip install plainml Example from plainml import KnnModel, load_ir
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
Decision Transformer: A brand new Offline RL Pattern
DecisionTransformer_StepbyStep Intro Decision Transformer: A brand new Offline RL Pattern. 这是关于NeurIPS 2021 热门论文Decision Transformer的复现。 👍 原文地址: Deci
TensorFlow implementation for Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How
Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How TensorFlow implementation for Bayesian Modeling and Unce
Using Self-Supervised Pretext Tasks for Active Learning - Official Pytorch Implementation
Using Self-Supervised Pretext Tasks for Active Learning - Official Pytorch Implementation Experiment Setting: CIFAR10 (downloaded and saved in ./DATA
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
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
CoINN: Correlated-informed neural networks: a new machine learning framework to predict pressure drop in micro-channels
CoINN: Correlated-informed neural networks: a new machine learning framework to predict pressure drop in micro-channels Accurate pressure drop estimat
Reinforcement Learning Theory Book (rus)
Reinforcement Learning Theory Book (rus)
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
Using Machine Learning to Test Causal Hypotheses in Conjoint Analysis
Readme File for "Using Machine Learning to Test Causal Hypotheses in Conjoint Analysis" by Ham, Imai, and Janson. (2022) All scripts were written and
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
JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine Translation
JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine Translation This the repository for this paper. Find extensions of this w
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
WPPNets: Unsupervised CNN Training with Wasserstein Patch Priors for Image Superresolution
WPPNets: Unsupervised CNN Training with Wasserstein Patch Priors for Image Superresolution This code belongs to the paper [1] available at https://arx
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
FaceOcc: A Diverse, High-quality Face Occlusion Dataset for Human Face Extraction
FaceExtraction FaceOcc: A Diverse, High-quality Face Occlusion Dataset for Human Face Extraction Occlusions often occur in face images in the wild, tr
DROPO: Sim-to-Real Transfer with Offline Domain Randomization
DROPO: Sim-to-Real Transfer with Offline Domain Randomization Gabriele Tiboni, Karol Arndt, Ville Kyrki. This repository contains the code for the pap
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
Tracking Progress in Question Answering over Knowledge Graphs
Tracking Progress in Question Answering over Knowledge Graphs Table of contents Question Answering Systems with Descriptions The QA Systems Table cont
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
Distance-Ratio-Based Formulation for Metric Learning
Distance-Ratio-Based Formulation for Metric Learning Environment Python3 Pytorch (http://pytorch.org/) (version 1.6.0+cu101) json tqdm Preparing datas
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
For encoding a text longer than 512 tokens, for example 800. Set max_pos to 800 during both preprocessing and training.
LongScientificFormer For encoding a text longer than 512 tokens, for example 800. Set max_pos to 800 during both preprocessing and training. Some code
PyTorch implementation for the paper Visual Representation Learning with Self-Supervised Attention for Low-Label High-Data Regime
Visual Representation Learning with Self-Supervised Attention for Low-Label High-Data Regime Created by Prarthana Bhattacharyya. Disclaimer: This is n
Bag of Tricks for Natural Policy Gradient Reinforcement Learning
Bag of Tricks for Natural Policy Gradient Reinforcement Learning [ArXiv] Setup Python 3.8.0 pip install -r req.txt Mujoco 200 license Main Files main.
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
PyTorch implementation of ICLR 2022 paper PiCO: Contrastive Label Disambiguation for Partial Label Learning
PiCO: Contrastive Label Disambiguation for Partial Label Learning This is a PyTorch implementation of ICLR 2022 paper PiCO: Contrastive Label Disambig
Learning to Predict Gradients for Semi-Supervised Continual Learning
Learning to Predict Gradients for Semi-Supervised Continual Learning Code for project: "Learning to Predict Gradients for Semi-Supervised Continual Le
Code for project: "Learning to Minimize Remainder in Supervised Learning".
Learning to Minimize Remainder in Supervised Learning Code for project: "Learning to Minimize Remainder in Supervised Learning". Requirements and Envi
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