3550 Repositories
Python deep-models Libraries
TGS Salt Identification Challenge
TGS Salt Identification Challenge This is an open solution to the TGS Salt Identification Challenge. Note Unfortunately, we can no longer provide supp
Airbus Ship Detection Challenge
Airbus Ship Detection Challenge This is an open solution to the Airbus Ship Detection Challenge. Our goals We are building entirely open solution to t
OCR-D wrapper for detectron2 based segmentation models
ocrd_detectron2 OCR-D wrapper for detectron2 based segmentation models Introduction Installation Usage OCR-D processor interface ocrd-detectron2-segm
Deep Learning: Architectures & Methods Project: Deep Learning for Audio Super-Resolution
Deep Learning: Architectures & Methods Project: Deep Learning for Audio Super-Resolution Figure: Example visualization of the method and baseline as a
Open solution to the Toxic Comment Classification Challenge
Starter code: Kaggle Toxic Comment Classification Challenge More competitions 🎇 Check collection of public projects 🎁 , where you can find multiple
Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents
Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents [Project Page] [Paper] [Video] Wenlong Huang1, Pieter Abbee
Deep Learning Topics with Computer Vision & NLP
Deep learning Udacity Course Deep Learning Topics with Computer Vision & NLP for the AWS Machine Learning Engineer Nanodegree Program Tasks are mostly
Deep Learning for Morphological Profiling
Deep Learning for Morphological Profiling An end-to-end implementation of a ML System for morphological profiling using self-supervised learning to di
TLXZoo - Pre-trained models based on TensorLayerX
Pre-trained models based on TensorLayerX. TensorLayerX is a multi-backend AI fra
This Deep Learning Model Predicts that from which disease you are suffering.
Deep-Learning-Project This Deep Learning Model Predicts that from which disease you are suffering. This Project Covers the Topics of Deep Learning Int
Blackstone is a spaCy model and library for processing long-form, unstructured legal text
Blackstone Blackstone is a spaCy model and library for processing long-form, unstructured legal text. Blackstone is an experimental research project f
GNES enables large-scale index and semantic search for text-to-text, image-to-image, video-to-video and any-to-any content form
GNES is Generic Neural Elastic Search, a cloud-native semantic search system based on deep neural network.
Transformer in Vision
Transformer-in-Vision Recent Transformer-based CV and related works. Welcome to comment/contribute! Keep updated. Resource SCENIC: A JAX Library for C
Full Transformer Framework for Robust Point Cloud Registration with Deep Information Interaction
Full Transformer Framework for Robust Point Cloud Registration with Deep Information Interaction. arxiv This repository contains python scripts for tr
Learning to Prompt for Continual Learning
Learning to Prompt for Continual Learning (L2P) Official Jax Implementation L2P is a novel continual learning technique which learns to dynamically pr
Tree Nested PyTorch Tensor Lib
DI-treetensor treetensor is a generalized tree-based tensor structure mainly developed by OpenDILab Contributors. Almost all the operation can be supp
FSL-Mate: A collection of resources for few-shot learning (FSL).
FSL-Mate is a collection of resources for few-shot learning (FSL). In particular, FSL-Mate currently contains FewShotPapers: a paper list which tracks
GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification
GalaXC GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification @InProceedings{Saini21, author = {Saini, D. and Jain,
Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning
Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning. Circuit Training is an open-s
The Official PyTorch Implementation of "VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models" (ICLR 2021 spotlight paper)
Official PyTorch implementation of "VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models" (ICLR 2021 Spotlight Paper) Zhisheng
PyTorch implementation of image classification models for CIFAR-10/CIFAR-100/MNIST/FashionMNIST/Kuzushiji-MNIST/ImageNet
PyTorch Image Classification Following papers are implemented using PyTorch. ResNet (1512.03385) ResNet-preact (1603.05027) WRN (1605.07146) DenseNet
T‘rex Park is a Youzan sponsored project. Offering Chinese NLP and image models pretrained from E-commerce datasets
T‘rex Park is a Youzan sponsored project. Offering Chinese NLP and image models pretrained from E-commerce datasets (product titles, images, comments, etc.).
TweebankNLP - Pre-trained Tweet NLP Pipeline (NER, tokenization, lemmatization, POS tagging, dependency parsing) + Models + Tweebank-NER
TweebankNLP This repo contains the new Tweebank-NER dataset and Twitter-Stanza p
ColossalAI-Examples - Examples of training models with hybrid parallelism using ColossalAI
ColossalAI-Examples This repository contains examples of training models with Co
Pipeline for employing a Lightweight deep learning models for LOW-power systems
PL-LOW A high-performance deep learning model lightweight pipeline that gradually lightens deep neural networks in order to utilize high-performance d
🚀 PyTorch Implementation of "Progressive Distillation for Fast Sampling of Diffusion Models(v-diffusion)"
PyTorch Implementation of "Progressive Distillation for Fast Sampling of Diffusion Models(v-diffusion)" Unofficial PyTorch Implementation of Progressi
cl;asification problem using classification models in supervised learning
wine-quality-predition---classification cl;asification problem using classification models in supervised learning Wine Quality Prediction Analysis - C
Learn Machine Learning Algorithms by doing projects in Python and R Programming Language
Learn Machine Learning Algorithms by doing projects in Python and R Programming Language. This repo covers all aspect of Machine Learning Algorithms.
Mortality risk prediction for COVID-19 patients using XGBoost models
Mortality risk prediction for COVID-19 patients using XGBoost models Using demographic and lab test data received from the HM Hospitales in Spain, I b
DeepFaceLive - Live Deep Fake in python, Real-time face swap for PC streaming or video calls
DeepFaceLive - Live Deep Fake in python, Real-time face swap for PC streaming or video calls
A handy tool for common machine learning models' hyper-parameter tuning.
Common machine learning models' hyperparameter tuning This repo is for a collection of hyper-parameter tuning for "common" machine learning models, in
TJU Deep Learning & Neural Network
Deep_Learning & Neural_Network_Lab 实验环境 Python 3.9 Anaconda3(官网下载或清华镜像都行) PyTorch 1.10.1(安装代码如下) conda install pytorch torchvision torchaudio cudatool
Can We Find Neurons that Cause Unrealistic Images in Deep Generative Networks?
Can We Find Neurons that Cause Unrealistic Images in Deep Generative Networks? Artifact Detection/Correction - Offcial PyTorch Implementation This rep
Official Code Release for "CLIP-Adapter: Better Vision-Language Models with Feature Adapters"
Official Code Release for "CLIP-Adapter: Better Vision-Language Models with Feature Adapters" Pipeline of CLIP-Adapter CLIP-Adapter is a drop-in modul
[内测中]前向式Python环境快捷封装工具,快速将Python打包为EXE并添加CUDA、NoAVX等支持。
QPT - Quick packaging tool 快捷封装工具 GitHub主页 | Gitee主页 QPT是一款可以“模拟”开发环境的多功能封装工具,最短只需一行命令即可将普通的Python脚本打包成EXE可执行程序,并选择性添加CUDA和NoAVX的支持,尽可能兼容更多的用户环境。 感觉还可
This is the repository for The Machine Learning Workshops, published by AI DOJO
This is the repository for The Machine Learning Workshops, published by AI DOJO. It contains all the workshop's code with supporting project files necessary to work through the code.
In this project, we compared Spanish BERT and Multilingual BERT in the Sentiment Analysis task.
Applying BERT Fine Tuning to Sentiment Classification on Amazon Reviews Abstract Sentiment analysis has made great progress in recent years, due to th
Brain Tumor Detection with Tensorflow Neural Networks.
Brain-Tumor-Detection A convolutional neural network model built with Tensorflow & Keras to detect brain tumor and its different variants. Data of the
The original weights of some Caffe models, ported to PyTorch.
pytorch-caffe-models This repo contains the original weights of some Caffe models, ported to PyTorch. Currently there are: GoogLeNet (Going Deeper wit
SynapseML - an open source library to simplify the creation of scalable machine learning pipelines
Synapse Machine Learning SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. Sy
Mixed Neural Likelihood Estimation for models of decision-making
Mixed neural likelihood estimation for models of decision-making Mixed neural likelihood estimation (MNLE) enables Bayesian parameter inference for mo
Animal Sound Classification (Cats Vrs Dogs Audio Sentiment Classification)
this is a simple artificial neural network model using deep learning and torch-audio to classify cats and dog sounds.
ParaGen is a PyTorch deep learning framework for parallel sequence generation
ParaGen is a PyTorch deep learning framework for parallel sequence generation. Apart from sequence generation, ParaGen also enhances various NLP tasks, including sequence-level classification, extraction and generation.
PyGRANSO: A PyTorch-enabled port of GRANSO with auto-differentiation
PyGRANSO PyGRANSO: A PyTorch-enabled port of GRANSO with auto-differentiation Please check https://ncvx.org/PyGRANSO for detailed instructions (introd
ML models and internal tensors 3D visualizer
The free Zetane Viewer is a tool to help understand and accelerate discovery in machine learning and artificial neural networks. It can be used to ope
Deep Learning for Time Series Forecasting.
nixtlats:Deep Learning for Time Series Forecasting [nikstla] (noun, nahuatl) Period of time. State-of-the-art time series forecasting for pytorch. Nix
Predicting 10 different clothing types using Xception pre-trained model.
Predicting-Clothing-Types Predicting 10 different clothing types using Xception pre-trained model from Keras library. It is reimplemented version from
In this Notebook I've build some machine-learning and deep-learning to classify corona virus tweets, in both multi class classification and binary classification.
Hello, This Notebook Contains Example of Corona Virus Tweets Multi Class Classification. - Classes is: Extremely Positive, Positive, Extremely Negativ
Implementation of ML models like Decision tree, Naive Bayes, Logistic Regression and many other
ML_Model_implementaion Implementation of ML models like Decision tree, Naive Bayes, Logistic Regression and many other dectree_model: Implementation o
Latent Network Models to Account for Noisy, Multiply-Reported Social Network Data
VIMuRe Latent Network Models to Account for Noisy, Multiply-Reported Social Network Data. If you use this code please cite this article (preprint). De
Deep deconfounded recommender (Deep-Deconf) for paper "Deep causal reasoning for recommendations"
Deep Causal Reasoning for Recommender Systems The codes are associated with the following paper: Deep Causal Reasoning for Recommendations, Yaochen Zh
"Exploring Vision Transformers for Fine-grained Classification" at CVPRW FGVC8
FGVC8 Exploring Vision Transformers for Fine-grained Classification paper presented at the CVPR 2021, The Eight Workshop on Fine-Grained Visual Catego
RETRO-pytorch - Implementation of RETRO, Deepmind's Retrieval based Attention net, in Pytorch
RETRO - Pytorch (wip) Implementation of RETRO, Deepmind's Retrieval based Attent
Pytorch code for "DPFM: Deep Partial Functional Maps" - 3DV 2021 (Oral)
DPFM Code for "DPFM: Deep Partial Functional Maps" - 3DV 2021 (Oral) Installation This implementation runs on python = 3.7, use pip to install depend
Reimplementation of Learning Mesh-based Simulation With Graph Networks
Pytorch Implementation of Learning Mesh-based Simulation With Graph Networks This is the unofficial implementation of the approach described in the pa
Deep learning transformer model that generates unique music sequences.
music-ai Deep learning transformer model that generates unique music sequences. Abstract In 2017, a new state-of-the-art was published for natural lan
Laplace Redux -- Effortless Bayesian Deep Learning
Laplace Redux - Effortless Bayesian Deep Learning This repository contains the code to run the experiments for the paper Laplace Redux - Effortless Ba
Tackling Obstacle Tower Challenge using PPO & A2C combined with ICM.
Obstacle Tower Challenge using Deep Reinforcement Learning Unity Obstacle Tower is a challenging realistic 3D, third person perspective and procedural
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
Implement of "Training deep neural networks via direct loss minimization" in PyTorch for 0-1 loss
This is the implementation of "Training deep neural networks via direct loss minimization" published at ICML 2016 in PyTorch. The implementation targe
Official PyTorch Implementation of "AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting".
AgentFormer This repo contains the official implementation of our paper: AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecast
As a part of the HAKE project, includes the reproduced SOTA models and the corresponding HAKE-enhanced versions (CVPR2020).
HAKE-Action HAKE-Action (TensorFlow) is a project to open the SOTA action understanding studies based on our Human Activity Knowledge Engine. It inclu
Implementation of Memory-Compressed Attention, from the paper "Generating Wikipedia By Summarizing Long Sequences"
Memory Compressed Attention Implementation of the Self-Attention layer of the proposed Memory-Compressed Attention, in Pytorch. This repository offers
An implementation of the efficient attention module.
Efficient Attention An implementation of the efficient attention module. Description Efficient attention is an attention mechanism that substantially
GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond
GCNet for Object Detection By Yue Cao, Jiarui Xu, Stephen Lin, Fangyun Wei, Han Hu. This repo is a official implementation of "GCNet: Non-local Networ
Pytorch implementation of Compressive Transformers, from Deepmind
Compressive Transformer in Pytorch Pytorch implementation of Compressive Transformers, a variant of Transformer-XL with compressed memory for long-ran
Implementation of Axial attention - attending to multi-dimensional data efficiently
Axial Attention Implementation of Axial attention in Pytorch. A simple but powerful technique to attend to multi-dimensional data efficiently. It has
Implementing SYNTHESIZER: Rethinking Self-Attention in Transformer Models using Pytorch
Implementing SYNTHESIZER: Rethinking Self-Attention in Transformer Models using Pytorch Reference Paper URL Author: Yi Tay, Dara Bahri, Donald Metzler
My take on a practical implementation of Linformer for Pytorch.
Linformer Pytorch Implementation A practical implementation of the Linformer paper. This is attention with only linear complexity in n, allowing for v
🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱
Monitor deep learning model training and hardware usage from mobile. 🔥 Features Monitor running experiments from mobile phone (or laptop) Monitor har
Official repository of "DeepMIH: Deep Invertible Network for Multiple Image Hiding", TPAMI 2022.
DeepMIH: Deep Invertible Network for Multiple Image Hiding (TPAMI 2022) This repo is the official code for DeepMIH: Deep Invertible Network for Multip
📚 A collection of all the Deep Learning Metrics that I came across which are not accuracy/loss.
📚 A collection of all the Deep Learning Metrics that I came across which are not accuracy/loss.
Node-level Graph Regression with Deep Gaussian Process Models
Node-level Graph Regression with Deep Gaussian Process Models Prerequests our implementation is mainly based on tensorflow 1.x and gpflow 1.x: python
Meta learning algorithms to train cross-lingual NLI (multi-task) models
Meta learning algorithms to train cross-lingual NLI (multi-task) models
Exploring Machine Learning Models for detecting anomalous behavior in credit-card transactions. It's crucial that credit-card companies are able to recognize fraudulent activity so that customers are not charged for items they didn't purchase.
Credit Card Fraud Detection Came across this mocked-up dataset of customer transactions at [Capital One Recruitment Challenge](https://github.com/Capi
Prediction of MBA refinance Index (Mortgage prepayment)
Prediction of MBA refinance Index (Mortgage prepayment) Deep Neural Network based Model The ability to predict mortgage prepayment is of critical use
Sentiment analysis translations of the Bhagavad Gita
Sentiment and Semantic Analysis of Bhagavad Gita Translations It is well known that translations of songs and poems not only breaks rhythm and rhyming
Repository containing the PhD Thesis "Formal Verification of Deep Reinforcement Learning Agents"
Getting Started This repository contains the code used for the following publications: Probabilistic Guarantees for Safe Deep Reinforcement Learning (
Unofficial JAX implementations of Deep Learning models
JAX Models Table of Contents About The Project Getting Started Prerequisites Installation Usage Contributing License Contact About The Project The JAX
A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base Population
DeepKE is a knowledge extraction toolkit supporting low-resource and document-level scenarios for entity, relation and attribute extraction. We provide comprehensive documents, Google Colab tutorials, and online demo for beginners.
This is the official implementation of our proposed SwinMR
SwinMR This is the official implementation of our proposed SwinMR: Swin Transformer for Fast MRI Please cite: @article{huang2022swin, title={Swi
Dimension Reduced Turbulent Flow Data From Deep Vector Quantizers
Dimension Reduced Turbulent Flow Data From Deep Vector Quantizers This is an implementation of A Physics-Informed Vector Quantized Autoencoder for Dat
Optical machine for senses sensing using speckle and deep learning
# Senses-speckle [Remote Photonic Detection of Human Senses Using Secondary Speckle Patterns](https://doi.org/10.21203/rs.3.rs-724587/v1) paper Python
Public Models considered for emotion estimation from EEG
Emotion-EEG Set of models for emotion estimation from EEG. Composed by the combination of two deep-learing models learning together (RNN and CNN) with
Similarity-based Gray-box Adversarial Attack Against Deep Face Recognition
Similarity-based Gray-box Adversarial Attack Against Deep Face Recognition Introduction Run attack: SGADV.py Objective function: foolbox/attacks/gradi
Source codes for Improved Few-Shot Visual Classification (CVPR 2020), Enhancing Few-Shot Image Classification with Unlabelled Examples
Source codes for Improved Few-Shot Visual Classification (CVPR 2020), Enhancing Few-Shot Image Classification with Unlabelled Examples (WACV 2022) and Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning (TPAMI 2022 - in submission)
Weakly Supervised Scene Text Detection using Deep Reinforcement Learning
Weakly Supervised Scene Text Detection using Deep Reinforcement Learning This repository contains the setup for all experiments performed in our Paper
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Awesome production machine learning This repository contains a curated list of awesome open source libraries that will help you deploy, monitor, versi
A curated list of awesome Deep Learning tutorials, projects and communities.
Awesome Deep Learning Table of Contents Books Courses Videos and Lectures Papers Tutorials Researchers Websites Datasets Conferences Frameworks Tools
An awesome Data Science repository to learn and apply for real world problems.
AWESOME DATA SCIENCE An open source Data Science repository to learn and apply towards solving real world problems. This is a shortcut path to start s
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
applied-ml Curated papers, articles, and blogs on data science & machine learning in production. ⚙️ Figuring out how to implement your ML project? Lea
Collection of machine learning related notebooks to share.
ML_Notebooks Collection of machine learning related notebooks to share. Notebooks GAN_distributed_training.ipynb In this Notebook, TensorFlow's tutori
Reference implementation for Structured Prediction with Deep Value Networks
Deep Value Network (DVN) This code is a python reference implementation of DVNs introduced in Deep Value Networks Learn to Evaluate and Iteratively Re
Deep Watershed Transform for Instance Segmentation
Deep Watershed Transform Performs instance level segmentation detailed in the following paper: Min Bai and Raquel Urtasun, Deep Watershed Transformati
FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics
FusionNet_Pytorch FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics Requirements Pytorch 0.1.11 Pyt
TransferNet: Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network
TransferNet: Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network Created by Seunghoon Hong, Junhyuk Oh,
Simple Tensorflow implementation of Toward Spatially Unbiased Generative Models (ICCV 2021)
Spatial unbiased GANs — Simple TensorFlow Implementation [Paper] : Toward Spatially Unbiased Generative Models (ICCV 2021) Abstract Recent image gener
A simple python module to generate anchor (aka default/prior) boxes for object detection tasks.
PyBx WIP A simple python module to generate anchor (aka default/prior) boxes for object detection tasks. Calculated anchor boxes are returned as ndarr
From Perceptron model to Deep Neural Network from scratch in Python.
Neural-Network-Basics Aim of this Repository: From Perceptron model to Deep Neural Network (from scratch) in Python. ** Currently working on a basic N
Pytorch implementation of MLP-Mixer with loading pre-trained models.
MLP-Mixer-Pytorch PyTorch implementation of MLP-Mixer: An all-MLP Architecture for Vision with the function of loading official ImageNet pre-trained p