3934 Repositories
Python deep-generative-model Libraries
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
Scripts used to make and evaluate OpenAlex's concept tagging model
openalex-concept-tagging This repository contains all of the code for getting the concept tagger up and running. To learn more about where this model
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
The model is designed to train a single and large neural network in order to predict correct translation by reading the given sentence.
Neural Machine Translation communication system The model is basically direct to convert one source language to another targeted language using encode
"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
BeautyNet is an AI powered model which can tell you whether you're beautiful or not.
BeautyNet BeautyNet is an AI powered model which can tell you whether you're beautiful or not. Download Dataset from here:https://www.kaggle.com/gpios
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
VGG16 model-based classification project about brain tumor detection.
Brain-Tumor-Classification-with-MRI VGG16 model-based classification project about brain tumor detection. First, you can check what people are doing o
Step by Step on how to create an vision recognition model using LOBE.ai, export the model and run the model in an Azure Function
Step by Step on how to create an vision recognition model using LOBE.ai, export the model and run the model in an Azure Function
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
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
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 natural language processing model for sequential sentence classification in medical abstracts.
NLP PubMed Medical Research Paper Abstract (Randomized Controlled Trial) A natural language processing model for sequential sentence classification in
📚 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
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
This is a model to classify Vietnamese sign language using Motion history image (MHI) algorithm and CNN.
Vietnamese sign lagnuage recognition using MHI and CNN This is a model to classify Vietnamese sign language using Motion history image (MHI) algorithm
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.
Source code for paper "Black-Box Tuning for Language-Model-as-a-Service"
Black-Box-Tuning Source code for paper "Black-Box Tuning for Language-Model-as-a-Service". Being busy recently, the code in this repo and this tutoria
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
Compartmental epidemic model to assess undocumented infections: applications to SARS-CoV-2 epidemics in Brazil - Datasets and Codes
Compartmental epidemic model to assess undocumented infections: applications to SARS-CoV-2 epidemics in Brazil - Datasets and Codes The codes for simu
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
VR Viewport Pose Model for Quantifying and Exploiting Frame Correlations
This repository contains the introduction to the collected VRViewportPose dataset and the code for the IEEE INFOCOM 2022 paper: "VR Viewport Pose Model for Quantifying and Exploiting Frame Correlations"
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
Code for Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task
BRATS 2021 Solution For Segmentation Task This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmenta
This repo generates the training data and the model for Morpheus-Deblend
Morpheus-Deblend This repo generates the training data and the model for Morpheus-Deblend. This is the active development repo for the project and as
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
Jingju baseline - A baseline model of our project of Beijing opera script generation
Jingju Baseline It is a baseline of our project about Beijing opera script gener
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,
Sentinel-1 vessel detection model used in the xView3 challenge
sar_vessel_detect Code for the AI2 Skylight team's submission in the xView3 competition (https://iuu.xview.us) for vessel detection in Sentinel-1 SAR
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
Using Global fishing watch's data to build a machine learning model that can identify illegal fishing and poaching activities through satellite and geo-location data.
Using Global fishing watch's data to build a machine learning model that can identify illegal fishing and poaching activities through satellite and geo-location data.
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
Book Recommender System Using Sci-kit learn N-neighbours
Model-Based-Recommender-Engine I created a book Recommender System using Sci-kit learn's N-neighbours algorithm for my model and the streamlit library
Madanalysis5 - A package for event file analysis and recasting of LHC results
Welcome to MadAnalysis 5 Outline What is MadAnalysis 5? Requirements Downloading
Generic Foreground Segmentation in Images
Pixel Objectness The following repository contains pretrained model for pixel objectness. Please visit our project page for the paper and visual resul
Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).
Weakly Supervised Segmentation with TensorFlow This repo contains a TensorFlow implementation of weakly supervised instance segmentation as described
Deep Learning for Human Part Discovery in Images - Chainer implementation
Deep Learning for Human Part Discovery in Images - Chainer implementation NOTE: This is not official implementation. Original paper is Deep Learning f
Code of the paper "Part Detector Discovery in Deep Convolutional Neural Networks" by Marcel Simon, Erik Rodner and Joachim Denzler
Part Detector Discovery This is the code used in our paper "Part Detector Discovery in Deep Convolutional Neural Networks" by Marcel Simon, Erik Rodne
Code for the paper 'A High Performance CRF Model for Clothes Parsing'.
Clothes Parsing Overview This code provides an implementation of the research paper: A High Performance CRF Model for Clothes Parsing Edgar Simo-S
Film review classification
Film review classification Решение задачи классификации отзывов на фильмы на положительные и отрицательные с помощью рекуррентных нейронных сетей 1. З
MOOSE (Multi-organ objective segmentation) a data-centric AI solution that generates multilabel organ segmentations to facilitate systemic TB whole-person research
MOOSE (Multi-organ objective segmentation) a data-centric AI solution that generates multilabel organ segmentations to facilitate systemic TB whole-person research.The pipeline is based on nn-UNet and has the capability to segment 120 unique tissue classes from a whole-body 18F-FDG PET/CT image.
auto_code_complete is a auto word-completetion program which allows you to customize it on your need
auto_code_complete v1.3 purpose and usage auto_code_complete is a auto word-completetion program which allows you to customize it on your needs. the m
Deep Ensemble Learning with Jet-Like architecture
Ransomware analysis using DEL with jet-like architecture comprising two CNN wings, a sparse AE tail, a non-linear PCA to produce a diverse feature space, and an MLP nose
Black-Box-Tuning - Black-Box Tuning for Language-Model-as-a-Service
Black-Box-Tuning Source code for paper "Black-Box Tuning for Language-Model-as-a
Cryptocurrency Prediction with Artificial Intelligence (Deep Learning via LSTM Neural Networks)
Cryptocurrency Prediction with Artificial Intelligence (Deep Learning via LSTM Neural Networks)- Emirhan BULUT
Stock-Prediction - prediction of stock market movements using sentiment analysis and deep learning.
Stock-Prediction- In this project, we aim to enhance the prediction of stock market movements using sentiment analysis and deep learning. We divide th
Food recognition model using convolutional neural network & computer vision
Food recognition model using convolutional neural network & computer vision. The goal is to match or beat the DeepFood Research Paper
A short and easy PyTorch implementation of E(n) Equivariant Graph Neural Networks
Simple implementation of Equivariant GNN A short implementation of E(n) Equivariant Graph Neural Networks for HOMO energy prediction. Just 50 lines of
STARCH compuets regional extreme storm physical characteristics and moisture balance based on spatiotemporal precipitation data from reanalysis or climate model data.
STARCH (Storm Tracking And Regional CHaracterization) STARCH computes regional extreme storm physical and moisture balance characteristics based on sp
The code succinctly shows how our ensemble learning based on deep learning CNN is used for LAM-avulsion-diagnosis.
deep-learning-LAM-avulsion-diagnosis The code succinctly shows how our ensemble learning based on deep learning CNN is used for LAM-avulsion-diagnosis
Image Recognition Model Generator
Takes a user-inputted query and generates a machine learning image recognition model that determines if an inputted image is or isn't their query
🧮 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
Training a Resilient Q-Network against Observational Interference, Causal Inference Q-Networks
Obs-Causal-Q-Network AAAI 2022 - Training a Resilient Q-Network against Observational Interference Preprint | Slides | Colab Demo | Environment Setup
💊 A 3D Generative Model for Structure-Based Drug Design (NeurIPS 2021)
A 3D Generative Model for Structure-Based Drug Design Coming soon... Citation @inproceedings{luo2021sbdd, title={A 3D Generative Model for Structu
Vector Quantized Diffusion Model for Text-to-Image Synthesis
Vector Quantized Diffusion Model for Text-to-Image Synthesis Due to company policy, I have to set microsoft/VQ-Diffusion to private for now, so I prov
Intel® Neural Compressor is an open-source Python library running on Intel CPUs and GPUs
Intel® Neural Compressor targeting to provide unified APIs for network compression technologies, such as low precision quantization, sparsity, pruning, knowledge distillation, across different deep learning frameworks to pursue optimal inference performance.
Deep motion generator collections
GenMotion GenMotion (/gen’motion/) is a Python library for making skeletal animations. It enables easy dataset loading and experiment sharing for synt
A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval
CLIP4CMR A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval The original data and pre-calculate
Generative Autoregressive, Normalized Flows, VAEs, Score-based models (GANVAS)
GANVAS-models This is an implementation of various generative models. It contains implementations of the following: Autoregressive Models: PixelCNN, G
This repository provides the official implementation of 'Learning to ignore: rethinking attention in CNNs' accepted in BMVC 2021.
inverse_attention This repository provides the official implementation of 'Learning to ignore: rethinking attention in CNNs' accepted in BMVC 2021. Le
Mapping a variable-length sentence to a fixed-length vector using BERT model
Are you looking for X-as-service? Try the Cloud-Native Neural Search Framework for Any Kind of Data bert-as-service Using BERT model as a sentence enc
Keras implementations of Generative Adversarial Networks.
This repository has gone stale as I unfortunately do not have the time to maintain it anymore. If you would like to continue the development of it as
AWS Serverless Application Model (SAM) is an open-source framework for building serverless applications
AWS Serverless Application Model (AWS SAM) The AWS Serverless Application Model (SAM) is an open-source framework for building serverless applications
Keras code and weights files for popular deep learning models.
Trained image classification models for Keras THIS REPOSITORY IS DEPRECATED. USE THE MODULE keras.applications INSTEAD. Pull requests will not be revi
YoloV3 Implemented in Tensorflow 2.0
YoloV3 Implemented in TensorFlow 2.0 This repo provides a clean implementation of YoloV3 in TensorFlow 2.0 using all the best practices. Key Features
This is code of book "Learn Deep Learning with PyTorch"
深度学习入门之PyTorch Learn Deep Learning with PyTorch 非常感谢您能够购买此书,这个github repository包含有深度学习入门之PyTorch的实例代码。由于本人水平有限,在写此书的时候参考了一些网上的资料,在这里对他们表示敬意。由于深度学习的技术在
Python Machine Learning Jupyter Notebooks (ML website)
Python Machine Learning Jupyter Notebooks (ML website) Dr. Tirthajyoti Sarkar, Fremont, California (Please feel free to connect on LinkedIn here) Also
A set of Deep Reinforcement Learning Agents implemented in Tensorflow.
Deep Reinforcement Learning Agents This repository contains a collection of reinforcement learning algorithms written in Tensorflow. The ipython noteb
Jupyter notebooks for using & learning Keras
deep-learning-with-keras-notebooks 這個github的repository主要是個人在學習Keras的一些記錄及練習。希望在學習過程中發現到一些好的資訊與範例也可以對想要學習使用 Keras來解決問題的同好,或是對深度學習有興趣的在學學生可以有一些方便理解與上手範例