1556 Repositories
Python multi-gpu-training Libraries
Crowd sourced training data for Rasa NLU models
NLU Training Data Crowd-sourced training data for the development and testing of Rasa NLU models. If you're interested in grabbing some data feel free
To propose and implement a multi-class classification approach to disaster assessment from the given data set of post-earthquake satellite imagery.
To propose and implement a multi-class classification approach to disaster assessment from the given data set of post-earthquake satellite imagery.
Multi-Modal Machine Learning toolkit based on PyTorch.
简体中文 | English TorchMM 简介 多模态学习工具包 TorchMM 旨在于提供模态联合学习和跨模态学习算法模型库,为处理图片文本等多模态数据提供高效的解决方案,助力多模态学习应用落地。 近期更新 2022.1.5 发布 TorchMM 初始版本 v1.0 特性 丰富的任务场景:工具
KIND: an Italian Multi-Domain Dataset for Named Entity Recognition
KIND (Kessler Italian Named-entities Dataset) KIND is an Italian dataset for Named-Entity Recognition. It contains more than one million tokens with t
Multi-Objective Reinforced Active Learning
Multi-Objective Reinforced Active Learning Dependencies wandb tqdm pytorch = 1.7.0 numpy = 1.20.0 scipy = 1.1.0 pycolab == 1.2 Weights and Biases O
This repo includes the supplementary of our paper "CEMENT: Incomplete Multi-View Weak-Label Learning with Long-Tailed Labels"
Supplementary Materials for CEMENT: Incomplete Multi-View Weak-Label Learning with Long-Tailed Labels This repository includes all supplementary mater
Source code and data in paper "MDFEND: Multi-domain Fake News Detection (CIKM'21)"
MDFEND: Multi-domain Fake News Detection This is an official implementation for MDFEND: Multi-domain Fake News Detection which has been accepted by CI
Implementations of LSTM: A Search Space Odyssey variants and their training results on the PTB dataset.
An LSTM Odyssey Code for training variants of "LSTM: A Search Space Odyssey" on Fomoro. Check out the blog post. Training Install TensorFlow. Clone th
BridgeGAN - Tensorflow implementation of Bridging the Gap between Label- and Reference-based Synthesis in Multi-attribute Image-to-Image Translation.
Bridging the Gap between Label- and Reference based Synthesis(ICCV 2021) Tensorflow implementation of Bridging the Gap between Label- and Reference-ba
Contrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)
Contrastive Unpaired Translation (CUT) video (1m) | video (10m) | website | paper We provide our PyTorch implementation of unpaired image-to-image tra
TSIT: A Simple and Versatile Framework for Image-to-Image Translation
TSIT: A Simple and Versatile Framework for Image-to-Image Translation This repository provides the official PyTorch implementation for the following p
SMIS - Semantically Multi-modal Image Synthesis(CVPR 2020)
Semantically Multi-modal Image Synthesis Project page / Paper / Demo Semantically Multi-modal Image Synthesis(CVPR2020). Zhen Zhu, Zhiliang Xu, Anshen
Official PyTorch implementation of the paper: DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample
DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample (ICCV 2021 Oral) Project | Paper Official PyTorch implementation of the pape
MDMM - Learning multi-domain multi-modality I2I translation
Multi-Domain Multi-Modality I2I translation Pytorch implementation of multi-modality I2I translation for multi-domains. The project is an extension to
AsymmetricGAN - Dual Generator Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
AsymmetricGAN for Image-to-Image Translation AsymmetricGAN Framework for Multi-Domain Image-to-Image Translation AsymmetricGAN Framework for Hand Gest
Pytorch implemenation of Stochastic Multi-Label Image-to-image Translation (SMIT)
SMIT: Stochastic Multi-Label Image-to-image Translation This repository provides a PyTorch implementation of SMIT. SMIT can stochastically translate a
AttentionGAN for Unpaired Image-to-Image Translation & Multi-Domain Image-to-Image Translation
AttentionGAN-v2 for Unpaired Image-to-Image Translation AttentionGAN-v2 Framework The proposed generator learns both foreground and background attenti
Tf alloc - Simplication of GPU allocation for Tensorflow2
tf_alloc Simpliying GPU allocation for Tensorflow Developer: korkite (Junseo Ko)
Augmented CLIP - Training simple models to predict CLIP image embeddings from text embeddings, and vice versa.
Train aug_clip against laion400m-embeddings found here: https://laion.ai/laion-400-open-dataset/ - note that this used the base ViT-B/32 CLIP model. S
TrainingBike - Code, models and schematics I've used to interface my stationary training bike with PC.
TrainingBike Code, models and schematics I've used to interface my stationary training bike with PC. You can find more information about the project i
BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work
BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work. For this project, I used the sigmoid function as an activation function along with stochastic gradient descent to adjust the weights and biases.
PyTorch-Multi-Style-Transfer - Neural Style and MSG-Net
PyTorch-Style-Transfer This repo provides PyTorch Implementation of MSG-Net (ours) and Neural Style (Gatys et al. CVPR 2016), which has been included
Keras Realtime Multi-Person Pose Estimation - Keras version of Realtime Multi-Person Pose Estimation project
This repository has become incompatible with the latest and recommended version of Tensorflow 2.0 Instead of refactoring this code painfully, I create
U-2-Net: U Square Net - Modified for paired image training of style transfer
U2-Net: U Square Net Modified for paired image training of style transfer This is an unofficial repo making use of the code which was made available b
Organseg dags - The repository contains the codebase for multi-organ segmentation with directed acyclic graphs (DAGs) in CT.
Organseg dags - The repository contains the codebase for multi-organ segmentation with directed acyclic graphs (DAGs) in CT.
Multi agent DDPG algorithm written in Python + Pytorch
Multi agent DDPG algorithm written in Python + Pytorch. It also includes a Jupyter notebook, Tennis.ipynb, as a showcase.
WebhookHub - A discord WebHook Manager with much more features coming soon
WebhookHub A discord WebHook Manager with much more features coming soon This is
Time-series-deep-learning - Developing Deep learning LSTM, BiLSTM models, and NeuralProphet for multi-step time-series forecasting of stock price.
Stock Price Prediction Using Deep Learning Univariate Time Series Predicting stock price using historical data of a company using Neural networks for
BRNet - code for Automated assessment of BI-RADS categories for ultrasound images using multi-scale neural networks with an order-constrained loss function
BRNet code for "Automated assessment of BI-RADS categories for ultrasound images using multi-scale neural networks with an order-constrained loss func
StyleGAN2-ADA-training-jupyter - Training custom datasets in styleGAN2-ADA by NVIDIA using Jupyter
styleGAN2-ADA-training-jupyter Training custom datasets in styleGAN2-ADA on Jupyter Official StyleGAN2-ADA by NIVIDIA Paper Training Generative Advers
CIFAR-10_train-test - training and testing codes for dataset CIFAR-10
CIFAR-10_train-test - training and testing codes for dataset CIFAR-10
Training Cifar-10 Classifier Using VGG16
opevcvdl-hw3 This project uses pytorch and Qt to achieve the requirements. Version Python 3.6 opencv-contrib-python 3.4.2.17 Matplotlib 3.1.1 pyqt5 5.
MLP-Numpy - A simple modular implementation of Multi Layer Perceptron in pure Numpy.
MLP-Numpy A simple modular implementation of Multi Layer Perceptron in pure Numpy. I used the Iris dataset from scikit-learn library for the experimen
MultiTaskLearning - Multi Task Learning for 3D segmentation
Multi Task Learning for 3D segmentation Perception stack of an Autonomous Drivin
Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend
Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend This project acts as both a tuto
SOTA easy to use PyTorch-based DL training library
Easily train or fine-tune SOTA computer vision models from one training repository. SuperGradients Introduction Welcome to SuperGradients, a free open
Class-imbalanced / Long-tailed ensemble learning in Python. Modular, flexible, and extensible
IMBENS: Class-imbalanced Ensemble Learning in Python Language: English | Chinese/中文 Links: Documentation | Gallery | PyPI | Changelog | Source | Downl
“Robust Lightweight Facial Expression Recognition Network with Label Distribution Training”, AAAI 2021.
EfficientFace Zengqun Zhao, Qingshan Liu, Feng Zhou. "Robust Lightweight Facial Expression Recognition Network with Label Distribution Training". AAAI
Aesara is a Python library that allows one to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.
Aesara is a Python library that allows one to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.
PyTorch Lightning + Hydra. A feature-rich template for rapid, scalable and reproducible ML experimentation with best practices. ⚡🔥⚡
Lightning-Hydra-Template A clean and scalable template to kickstart your deep learning project 🚀 ⚡ 🔥 Click on Use this template to initialize new re
Offical implementation of Shunted Self-Attention via Multi-Scale Token Aggregation
Shunted Transformer This is the offical implementation of Shunted Self-Attention via Multi-Scale Token Aggregation by Sucheng Ren, Daquan Zhou, Shengf
Python implementation of "Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation"
MIPNet: Multi-Instance Pose Networks This repository is the official pytorch python implementation of "Multi-Instance Pose Networks: Rethinking Top-Do
Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
A simple consistency training framework for semi-supervised image semantic segmentation
PseudoSeg: Designing Pseudo Labels for Semantic Segmentation PseudoSeg is a simple consistency training framework for semi-supervised image semantic s
Semi-Supervised Semantic Segmentation with Cross-Consistency Training (CCT)
Semi-Supervised Semantic Segmentation with Cross-Consistency Training (CCT) Paper, Project Page This repo contains the official implementation of CVPR
Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order of magnitude using coresets and data selection.
COResets and Data Subset selection Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order
Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition (NeurIPS 2019)
MLCR This is the source code for paper Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition. Xuesong Niu, Hu Han, Shiguang
Implementation of ICLR 2020 paper "Revisiting Self-Training for Neural Sequence Generation"
Self-Training for Neural Sequence Generation This repo includes instructions for running noisy self-training algorithms from the following paper: Revi
implementation of the paper "MarginGAN: Adversarial Training in Semi-Supervised Learning"
MarginGAN This repository is the implementation of the paper "MarginGAN: Adversarial Training in Semi-Supervised Learning". 1."preliminary" is the imp
Training neural models with structured signals.
Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured
PyTorch implementation for Graph Contrastive Learning with Augmentations
Graph Contrastive Learning with Augmentations PyTorch implementation for Graph Contrastive Learning with Augmentations [poster] [appendix] Yuning You*
CCCL: Contrastive Cascade Graph Learning.
CCGL: Contrastive Cascade Graph Learning This repo provides a reference implementation of Contrastive Cascade Graph Learning (CCGL) framework as descr
Memory-efficient optimum einsum using opt_einsum planning and PyTorch kernels.
opt-einsum-torch There have been many implementations of Einstein's summation. numpy's numpy.einsum is the least efficient one as it only runs in sing
A simplistic and efficient pure-python neural network library from Phys Whiz with CPU and GPU support.
A simplistic and efficient pure-python neural network library from Phys Whiz with CPU and GPU support.
In this project, two programs can help you take full agvantage of time on the model training with a remote server
In this project, two programs can help you take full agvantage of time on the model training with a remote server, which can push notification to your phone about the information during model training, like the model indices and unexpected interrupts. Then you can do something in time for your work.
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training @ KDD 2020
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training Original implementation for paper GCC: Graph Contrastive Coding for Graph Neural N
Pytorch implementation of the paper "COAD: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking."
Expert-Linking Pytorch implementation of the paper "COAD: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking." This is
Contrastive Multi-View Representation Learning on Graphs
Contrastive Multi-View Representation Learning on Graphs This work introduces a self-supervised approach based on contrastive multi-view learning to l
Scalable and Elastic Deep Reinforcement Learning Using PyTorch. Please star. 🔥
ElegantRL “小雅”: Scalable and Elastic Deep Reinforcement Learning ElegantRL is developed for researchers and practitioners with the following advantage
This project aim to create multi-label classification annotation tool to boost annotation speed and make it more easier.
This project aim to create multi-label classification annotation tool to boost annotation speed and make it more easier.
A multi-purpose Discord bot with simple moderation commands, reaction roles, reminders, and much more!
Nokari This is the rewrite of Nokari. There are still a lot of things to be done. I'm still working on the internal logic, so the bot basically has no
Minecraft Multi-Server Pinger Discord Embed
Minecraft Network Pinger Minecraft Multi-Server Pinger Discord Embed What does this bot do? It sends an embed and uses mcsrvstat API and checks if the
Code for "Intra-hour Photovoltaic Generation Forecasting based on Multi-source Data and Deep Learning Methods."
pv_predict_unet-lstm Code for "Intra-hour Photovoltaic Generation Forecasting based on Multi-source Data and Deep Learning Methods." IEEE Transactions
Reproduce results and replicate training fo T0 (Multitask Prompted Training Enables Zero-Shot Task Generalization)
T-Zero This repository serves primarily as codebase and instructions for training, evaluation and inference of T0. T0 is the model developed in Multit
Align and Prompt: Video-and-Language Pre-training with Entity Prompts
ALPRO Align and Prompt: Video-and-Language Pre-training with Entity Prompts [Paper] Dongxu Li, Junnan Li, Hongdong Li, Juan Carlos Niebles, Steven C.H
An Official Repo of CVPR '20 "MSeg: A Composite Dataset for Multi-Domain Segmentation"
This is the code for the paper: MSeg: A Composite Dataset for Multi-domain Semantic Segmentation (CVPR 2020, Official Repo) [CVPR PDF] [Journal PDF] J
Official release of MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis of Pancreatic Cancer axriv: http://arxiv.org/abs/2112.13513
MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis This is the official page of the MSHT with its experimental script and records. We de
Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation.
Pretrain-Recsys This is our Tensorflow implementation for our WSDM 2021 paper: Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li, Hong Chen. Pre-Training
Pre-training of Graph Augmented Transformers for Medication Recommendation
G-Bert Pre-training of Graph Augmented Transformers for Medication Recommendation Intro G-Bert combined the power of Graph Neural Networks and BERT (B
Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"
GPT-GNN: Generative Pre-Training of Graph Neural Networks GPT-GNN is a pre-training framework to initialize GNNs by generative pre-training. It can be
Reference Code for AAAI-20 paper "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels"
Reference Code for AAAI-20 paper "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels" Please refer to htt
code for "Self-supervised edge features for improved Graph Neural Network training", arxivlink
Self-supervised edge features for improved Graph Neural Network training Data availability: Here is a link to the raw data for the organoids dataset.
[ICML 2020] DrRepair: Learning to Repair Programs from Error Messages
DrRepair: Learning to Repair Programs from Error Messages This repo provides the source code & data of our paper: Graph-based, Self-Supervised Program
Autoregressive Predictive Coding: An unsupervised autoregressive model for speech representation learning
Autoregressive Predictive Coding This repository contains the official implementation (in PyTorch) of Autoregressive Predictive Coding (APC) proposed
Code and training data for our ECCV 2016 paper on Unsupervised Learning
Shuffle and Learn (Shuffle Tuple) Created by Ishan Misra Based on the ECCV 2016 Paper - "Shuffle and Learn: Unsupervised Learning using Temporal Order
[NeurIPS'20] Self-supervised Co-Training for Video Representation Learning. Tengda Han, Weidi Xie, Andrew Zisserman.
CoCLR: Self-supervised Co-Training for Video Representation Learning This repository contains the implementation of: InfoNCE (MoCo on videos) UberNCE
PyTorch code for training MM-DistillNet for multimodal knowledge distillation
There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge MM-DistillNet is a
Multi-task Self-supervised Object Detection via Recycling of Bounding Box Annotations (CVPR, 2019)
Multi-task Self-supervised Object Detection via Recycling of Bounding Box Annotations (CVPR 2019) To make better use of given limited labels, we propo
A multi purpose discord bot for python
Sypher The best multi purpose discord bot. Add Sypher right now Invite Me | Join
AdaFocus V2: End-to-End Training of Spatial Dynamic Networks for Video Recognition
AdaFocusV2 This repo contains the official code and pre-trained models for AdaFo
Deep Learning Training Scripts With Python
Deep Learning Training Scripts DNN Frameworks Caffe PyTorch Tensorflow CNN Models VGG ResNet DenseNet Inception Language Modeling GatedCNN-LM Attentio
A python-based multi-player online educational game for students to play in a class or club setting.
Kurono (codename: aimmo) Code for Life has been developed by Ocado Technology as a free, open-source project to inspire the next generation of compute
TE-dependent analysis (tedana) is a Python library for denoising multi-echo functional magnetic resonance imaging (fMRI) data
tedana: TE Dependent ANAlysis TE-dependent analysis (tedana) is a Python library for denoising multi-echo functional magnetic resonance imaging (fMRI)
The Multi-Tool Web Vulnerability Scanner.
🟥 RapidScan v1.2 - The Multi-Tool Web Vulnerability Scanner RapidScan has been ported to Python3 i.e. v1.2. The Python2.7 codebase is available on v1
Implementation of Memory-Efficient Neural Networks with Multi-Level Generation, ICCV 2021
Memory-Efficient Multi-Level In-Situ Generation (MLG) By Jiaqi Gu, Hanqing Zhu, Chenghao Feng, Mingjie Liu, Zixuan Jiang, Ray T. Chen and David Z. Pan
Hub is a dataset format with a simple API for creating, storing, and collaborating on AI datasets of any size.
Hub is a dataset format with a simple API for creating, storing, and collaborating on AI datasets of any size. The hub data layout enables rapid transformations and streaming of data while training models at scale. Hub is used by Google, Waymo, Red Cross, Oxford University, and Omdena.
Simple and Robust Loss Design for Multi-Label Learning with Missing Labels
Simple and Robust Loss Design for Multi-Label Learning with Missing Labels Official PyTorch Implementation of the paper Simple and Robust Loss Design
Antchain-MPC is a library of MPC (Multi-Parties Computation)
Antchain-MPC Antchain-MPC is a library of MPC (Multi-Parties Computation). It include Morse-STF: A tool for machine learning using MPC. Others: Commin
Baleen: Robust Multi-Hop Reasoning at Scale via Condensed Retrieval (NeurIPS'21)
Baleen Baleen is a state-of-the-art model for multi-hop reasoning, enabling scalable multi-hop search over massive collections for knowledge-intensive
Multi-Probe Attention for Semantic Indexing
Multi-Probe Attention for Semantic Indexing About This project is developed for the topic of COVID-19 semantic indexing. Directories & files A. The di
Code to use Augmented Shapiro Wilks Stopping, as well as code for the paper "Statistically Signifigant Stopping of Neural Network Training"
This codebase is being actively maintained, please create and issue if you have issues using it Basics All data files are included under losses and ea
A flexible data historian based on InfluxDB, Grafana, MQTT and more. Free, open, simple.
Kotori Telemetry data acquisition and sensor networks for humans. Documentation: https://getkotori.org/ Source Code: https://github.com/daq-tools/koto
PyTorch implementation of Rethinking Positional Encoding in Language Pre-training
TUPE PyTorch implementation of Rethinking Positional Encoding in Language Pre-training. Quickstart Clone this repository. git clone https://github.com
A local Socks5 server written in python, used for integrating Multi-hop
proxy-Zata proxy-Zata v1.0 This is a local Socks5 server written in python, used for integrating Multi-hop (Socks4/Socks5/HTTP) forward proxy then pro
An advanced multi-threaded, multi-client python reverse shell for hacking linux systems
PwnLnX An advanced multi-threaded, multi-client python reverse shell for hacking linux systems. There's still more work to do so feel free to help out
Code release for SLIP Self-supervision meets Language-Image Pre-training
SLIP: Self-supervision meets Language-Image Pre-training What you can find in this repo: Pre-trained models (with ViT-Small, Base, Large) and code to
Weakly Supervised End-to-End Learning (NeurIPS 2021)
WeaSEL: Weakly Supervised End-to-end Learning This is a PyTorch-Lightning-based framework, based on our End-to-End Weak Supervision paper (NeurIPS 202
Basic flask system for login, api, and status system
Flask Multi Site With Login This is a basic website login system with an uncomplete api system NOTICE : This is NOT complete and is made to be a bare
Turn any live video stream or locally stored video into a dataset of interesting samples for ML training, or any other type of analysis.
Sieve Video Data Collection Example Find samples that are interesting within hours of raw video, for free and completely automatically using Sieve API
Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning
Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning This is the code for implementing the MADDPG algorithm presented in