1454 Repositories
Python Multi-Head-Co-Training Libraries
CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator
CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator This is the official code repository for NeurIPS 2021 paper: CARMS: Categorica
Open source single image super-resolution toolbox containing various functionality for training a diverse number of state-of-the-art super-resolution models. Also acts as the companion code for the IEEE signal processing letters paper titled 'Improving Super-Resolution Performance using Meta-Attention Layers’.
Deep-FIR Codebase - Super Resolution Meta Attention Networks About This repository contains the main coding framework accompanying our work on meta-at
This is the official implementation for the paper "Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization" in NeurIPS 2021.
MPMAB_BEACON This is code used for the paper "Decentralized Multi-player Multi-armed Bandits: Beyond Linear Reward Functions", Neurips 2021. Requireme
[v1 (ISBI'21) + v2] MedMNIST: A Large-Scale Lightweight Benchmark for 2D and 3D Biomedical Image Classification
MedMNIST Project (Website) | Dataset (Zenodo) | Paper (arXiv) | MedMNIST v1 (ISBI'21) Jiancheng Yang, Rui Shi, Donglai Wei, Zequan Liu, Lin Zhao, Bili
Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks
Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks Setup This implementation is based on PyTorch = 1.0.0. Smal
SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs
SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs SMORE is a a versatile framework that scales multi-hop query emb
Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training
ColossalAI An integrated large-scale model training system with efficient parallelization techniques. arXiv: Colossal-AI: A Unified Deep Learning Syst
API for concurrency connections
Multi-connection-server-API API for concurrency connections difference between this server and the echo server is the call to lsock.setblocking(False)
A pre-trained model with multi-exit transformer architecture.
ElasticBERT This repository contains finetuning code and checkpoints for ElasticBERT. Towards Efficient NLP: A Standard Evaluation and A Strong Baseli
Data, model training, and evaluation code for "PubTables-1M: Towards a universal dataset and metrics for training and evaluating table extraction models".
PubTables-1M This repository contains training and evaluation code for the paper "PubTables-1M: Towards a universal dataset and metrics for training a
ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs
ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs This is the code of paper ConE: Cone Embeddings for Multi-Hop Reasoning over Knowl
Speed up your typing by some exercises in the multi-platform(Windows/Ubuntu).
Introduction This project purpose is speed up your typing by some exercises in the multi-platform(Windows/Ubuntu). Build Environment Software Environm
Predicting lncRNA–protein interactions based on graph autoencoders and collaborative training
Predicting lncRNA–protein interactions based on graph autoencoders and collaborative training Code for our paper "Predicting lncRNA–protein interactio
Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training
ColossalAI An integrated large-scale model training system with efficient parallelization techniques Installation PyPI pip install colossalai Install
AugMax: Adversarial Composition of Random Augmentations for Robust Training
[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.
ElasticBERT: A pre-trained model with multi-exit transformer architecture.
This repository contains finetuning code and checkpoints for ElasticBERT. Towards Efficient NLP: A Standard Evaluation and A Strong Baseli
MultiMix: Sparingly Supervised, Extreme Multitask Learning From Medical Images (ISBI 2021, MELBA 2021)
MultiMix This repository contains the implementation of MultiMix. Our publications for this project are listed below: "MultiMix: Sparingly Supervised,
Code of the paper "Multi-Task Meta-Learning Modification with Stochastic Approximation".
Multi-Task Meta-Learning Modification with Stochastic Approximation This repository contains the code for the paper "Multi-Task Meta-Learning Modifica
Exponential Graph is Provably Efficient for Decentralized Deep Training
Exponential Graph is Provably Efficient for Decentralized Deep Training This code repository is for the paper Exponential Graph is Provably Efficient
Implementation of several Bayesian multi-target tracking algorithms, including Poisson multi-Bernoulli mixture filters for sets of targets and sets of trajectories. The repository also includes the GOSPA metric and a metric for sets of trajectories to evaluate performance.
This repository contains the Matlab implementations for the following multi-target filtering/tracking algorithms: - Folder PMBM contains the implemen
[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.
AugMax: Adversarial Composition of Random Augmentations for Robust Training Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Anima Anandkumar, an
Code accompanying the paper Shared Independent Component Analysis for Multi-subject Neuroimaging
ShICA Code accompanying the paper Shared Independent Component Analysis for Multi-subject Neuroimaging Install Move into the ShICA directory cd ShICA
Code for AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Network (ICCV 2021).
AA-RMVSNet Code for AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Network (ICCV 2021) in PyTorch. paper link: arXiv | CVF Change Log Ju
In this project I played with mlflow, streamlit and fastapi to create a training and prediction app on digits
Fastapi + MLflow + streamlit Setup env. I hope I covered all. pip install -r requirements.txt Start app Go in the root dir and run these Streamlit str
YOLOv5 Series Multi-backbone, Pruning and quantization Compression Tool Box.
YOLOv5-Compression Update News Requirements 环境安装 pip install -r requirements.txt Evaluation metric Visdrone Model mAP mAP@50 Parameters(M) GFLOPs FPS@
Asterisk is a framework to generate high-quality training datasets at scale
Asterisk is a framework to generate high-quality training datasets at scale
Multi-layer convolutional LSTM with Pytorch
Convolution_LSTM_pytorch Thanks for your attention. I haven't got time to maintain this repo for a long time. I recommend this repo which provides an
[NeurIPS 2021] Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training
Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training Code for NeurIPS 2021 paper "Better Safe Than Sorry: Preventing Delu
This GitHub repository contains code used for plots in NeurIPS 2021 paper 'Stochastic Multi-Armed Bandits with Control Variates.'
About Repository This repository contains code used for plots in NeurIPS 2021 paper 'Stochastic Multi-Armed Bandits with Control Variates.' About Code
Code repository for the work "Multi-Domain Incremental Learning for Semantic Segmentation", accepted at WACV 2022
Multi-Domain Incremental Learning for Semantic Segmentation This is the Pytorch implementation of our work "Multi-Domain Incremental Learning for Sema
code for generating data set ES-ImageNet with corresponding training code
es-imagenet-master code for generating data set ES-ImageNet with corresponding training code dataset generator some codes of ODG algorithm The variabl
A Context-aware Visual Attention-based training pipeline for Object Detection from a Webpage screenshot!
CoVA: Context-aware Visual Attention for Webpage Information Extraction Abstract Webpage information extraction (WIE) is an important step to create k
Code for the prototype tool in our paper "CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning".
CoProtector Code for the prototype tool in our paper "CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning".
A novel pipeline framework for multi-hop complex KGQA task. About the paper title: Improving Multi-hop Embedded Knowledge Graph Question Answering by Introducing Relational Chain Reasoning
Rce-KGQA A novel pipeline framework for multi-hop complex KGQA task. This framework mainly contains two modules, answering_filtering_module and relati
Code for "AutoMTL: A Programming Framework for Automated Multi-Task Learning"
AutoMTL: A Programming Framework for Automated Multi-Task Learning This is the website for our paper "AutoMTL: A Programming Framework for Automated M
An example showing how to use jax to train resnet50 on multi-node multi-GPU
jax-multi-gpu-resnet50-example This repo shows how to use jax for multi-node multi-GPU training. The example is adapted from the resnet50 example in d
Code for the prototype tool in our paper "CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning".
CoProtector Code for the prototype tool in our paper "CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning".
Wanli Li and Tieyun Qian: Exploit a Multi-head Reference Graph for Semi-supervised Relation Extraction, IJCNN 2021
MRefG Wanli Li and Tieyun Qian: "Exploit a Multi-head Reference Graph for Semi-supervised Relation Extraction", IJCNN 2021 1. Requirements To reproduc
Unofficial PyTorch Implementation of Multi-Singer
Multi-Singer Unofficial PyTorch Implementation of Multi-Singer: Fast Multi-Singer Singing Voice Vocoder With A Large-Scale Corpus. Requirements See re
MVFNet: Multi-View Fusion Network for Efficient Video Recognition (AAAI 2021)
MVFNet: Multi-View Fusion Network for Efficient Video Recognition (AAAI 2021) Overview We release the code of the MVFNet (Multi-View Fusion Network).
This is the official source code for SLATE. We provide the code for the model, the training code, and a dataset loader for the 3D Shapes dataset. This code is implemented in Pytorch.
SLATE This is the official source code for SLATE. We provide the code for the model, the training code and a dataset loader for the 3D Shapes dataset.
PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Condition Layer Normalization and Semi-Supervised Training in Text-To-Speech
Cross-Speaker-Emotion-Transfer - PyTorch Implementation PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Conditio
pytorch implementation of the ICCV'21 paper "MVTN: Multi-View Transformation Network for 3D Shape Recognition"
MVTN: Multi-View Transformation Network for 3D Shape Recognition (ICCV 2021) By Abdullah Hamdi, Silvio Giancola, Bernard Ghanem Paper | Video | Tutori
PyTorch Code for NeurIPS 2021 paper Anti-Backdoor Learning: Training Clean Models on Poisoned Data.
Anti-Backdoor Learning PyTorch Code for NeurIPS 2021 paper Anti-Backdoor Learning: Training Clean Models on Poisoned Data. Check the unlearning effect
Efficient Training of Visual Transformers with Small Datasets
Official codes for "Efficient Training of Visual Transformers with Small Datasets", NerIPS 2021.
This code uses generative adversarial networks to generate diverse task allocation plans for Multi-agent teams.
Mutli-agent task allocation This code uses generative adversarial networks to generate diverse task allocation plans for Multi-agent teams. To change
Pyrin is an application framework built on top of Flask micro-framework to make life easier for developers who want to develop an enterprise application using Flask
Pyrin A rich, fast, performant and easy to use application framework to build apps using Flask on top of it. Pyrin is an application framework built o
Official code for MPG2: Multi-attribute Pizza Generator: Cross-domain Attribute Control with Conditional StyleGAN
This is the official code for Multi-attribute Pizza Generator (MPG2): Cross-domain Attribute Control with Conditional StyleGAN. Paper Demo Setup Envir
This is the code of "Multi-view Contrastive Graph Clustering" in NeurlPS 2021.
MCGC Description This is the code of "Multi-view Contrastive Graph Clustering" in NeurlPS 2021. Datasets Results ACM DBLP IMDB Amazon photos Amazon co
Training Very Deep Neural Networks Without Skip-Connections
DiracNets v2 update (January 2018): The code was updated for DiracNets-v2 in which we removed NCReLU by adding per-channel a and b multipliers without
PyTorch implementation of Octave Convolution with pre-trained Oct-ResNet and Oct-MobileNet models
octconv.pytorch PyTorch implementation of Octave Convolution in Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octa
Training RNNs as Fast as CNNs
News SRU++, a new SRU variant, is released. [tech report] [blog] The experimental code and SRU++ implementation are available on the dev branch which
A multi-mode modulator for multi-domain few-shot classification (ICCV)
A multi-mode modulator for multi-domain few-shot classification (ICCV)
A multi-page streamlit app for the geospatial community.
A multi-page streamlit app for the geospatial community.
New multi tool im making adding features currently
Emera Multi Tool New multi tool im making adding features currently Current List of Planned Features - Linkvertise Bypasser - Discord Auto Bump - Gith
CVNets: A library for training computer vision networks
CVNets: A library for training computer vision networks This repository contains the source code for training computer vision models. Specifically, it
Official implementation for the paper: "Multi-label Classification with Partial Annotations using Class-aware Selective Loss"
Multi-label Classification with Partial Annotations using Class-aware Selective Loss Paper | Pretrained models Official PyTorch Implementation Emanuel
A lightweight Python-based 3D network multi-agent simulator. Uses a cell-based congestion model. Calculates risk, loudness and battery capacities of the agents. Suitable for 3D network optimization tasks.
AMAZ3DSim AMAZ3DSim is a lightweight python-based 3D network multi-agent simulator. It uses a cell-based congestion model. It calculates risk, battery
Bootstrapped Unsupervised Sentence Representation Learning (ACL 2021)
Install first pip3 install -e . Training python3 training/unsupervised_tuning.py python3 training/supervised_tuning.py python3 training/multilingual_
BERT model training impelmentation using 1024 A100 GPUs for MLPerf Training v1.1
Pre-trained checkpoint and bert config json file Location of checkpoint and bert config json file This MLCommons members Google Drive location contain
Reimplementation of Dynamic Multi-scale filters for Semantic Segmentation.
Paddle implementation of Dynamic Multi-scale filters for Semantic Segmentation.
For auto aligning, cropping, and scaling HR and LR images for training image based neural networks
ImgAlign For auto aligning, cropping, and scaling HR and LR images for training image based neural networks Usage Make sure OpenCV is installed, 'pip
Unofficial implementation of MUSIQ (Multi-Scale Image Quality Transformer)
MUSIQ: Multi-Scale Image Quality Transformer Unofficial pytorch implementation of the paper "MUSIQ: Multi-Scale Image Quality Transformer" (paper link
NAS-HPO-Bench-II is the first benchmark dataset for joint optimization of CNN and training HPs.
NAS-HPO-Bench-II API Overview NAS-HPO-Bench-II is the first benchmark dataset for joint optimization of CNN and training HPs. It helps a fair and low-
Extremely simple and fast extreme multi-class and multi-label classifiers.
napkinXC napkinXC is an extremely simple and fast library for extreme multi-class and multi-label classification, that focus of implementing various m
Improving Non-autoregressive Generation with Mixup Training
MIST Training MIST TRAIN_FILE=/your/path/to/train.json VALID_FILE=/your/path/to/valid.json OUTPUT_DIR=/your/path/to/save_checkpoints CACHE_DIR=/your/p
Official implementation for the paper: Multi-label Classification with Partial Annotations using Class-aware Selective Loss
Multi-label Classification with Partial Annotations using Class-aware Selective Loss Paper | Pretrained models Official PyTorch Implementation Emanuel
NeurIPS'21: Probabilistic Margins for Instance Reweighting in Adversarial Training (Pytorch implementation).
source code for NeurIPS21 paper robabilistic Margins for Instance Reweighting in Adversarial Training
Code release for "Cycle Self-Training for Domain Adaptation" (NeurIPS 2021)
CST Code release for "Cycle Self-Training for Domain Adaptation" (NeurIPS 2021) Prerequisites torch=1.7.0 torchvision qpsolvers numpy prettytable tqd
Pytorch implementation for "Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets" (ECCV 2020 Spotlight)
Distribution-Balanced Loss [Paper] The implementation of our paper Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets (
A library for preparing, training, and evaluating scalable deep learning hybrid recommender systems using PyTorch.
collie Collie is a library for preparing, training, and evaluating implicit deep learning hybrid recommender systems, named after the Border Collie do
A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)
MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-t
Implementation of EMNLP 2017 Paper "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog" using PyTorch and ParlAI
Language Emergence in Multi Agent Dialog Code for the Paper Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog Satwik Kottur, José M.
A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model Deployment.
chitra What is chitra? chitra (चित्र) is a multi-functional library for full-stack Deep Learning. It simplifies Model Building, API development, and M
Permeability Prediction Via Multi Scale 3D CNN
Permeability-Prediction-Via-Multi-Scale-3D-CNN Data: The raw CT rock cores are obtained from the Imperial Colloge portal. The CT rock cores are sub-sa
Supplemental Code for "ImpressionNet :A Multi view Approach to Predict Socio Facial Impressions"
Supplemental Code for "ImpressionNet :A Multi view Approach to Predict Socio Facial Impressions" Environment requirement This code is based on Python
Deep learning library for solving differential equations and more
DeepXDE Voting on whether we should have a Slack channel for discussion. DeepXDE is a library for scientific machine learning. Use DeepXDE if you need
QuakeLabeler is a Python package to create and manage your seismic training data, processes, and visualization in a single place — so you can focus on building the next big thing.
QuakeLabeler Quake Labeler was born from the need for seismologists and developers who are not AI specialists to easily, quickly, and independently bu
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa
Project code for weakly supervised 3D object detectors using wide-baseline multi-view traffic camera data: WIBAM.
WIBAM (Work in progress) Weakly Supervised Training of Monocular 3D Object Detectors Using Wide Baseline Multi-view Traffic Camera Data 3D object dete
The official code for PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization
PRIMER The official code for PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization. PRIMER is a pre-trained model for mu
A Partition Filter Network for Joint Entity and Relation Extraction EMNLP 2021
EMNLP 2021 - A Partition Filter Network for Joint Entity and Relation Extraction
A plugin to simplify creating multi-page Dash apps
Multi-Page Dash App Plugin A plugin to simplify creating multi-page Dash apps. This is a preview of functionality that will of Dash 2.1. Background Th
Implements the training, testing and editing tools for "Pluralistic Image Completion"
Pluralistic Image Completion ArXiv | Project Page | Online Demo | Video(demo) This repository implements the training, testing and editing tools for "
A Deep Learning based project for creating line art portraits.
ArtLine The main aim of the project is to create amazing line art portraits. Sounds Intresting,let's get to the pictures!! Model-(Smooth) Model-(Quali
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more
PyTorch Image Models Sponsors What's New Introduction Models Features Results Getting Started (Documentation) Train, Validation, Inference Scripts Awe
Synthetic structured data generators
Join us on What is Synthetic Data? Synthetic data is artificially generated data that is not collected from real world events. It replicates the stati
Source code for the paper "PLOME: Pre-training with Misspelled Knowledge for Chinese Spelling Correction" in ACL2021
PLOME:Pre-training with Misspelled Knowledge for Chinese Spelling Correction (ACL2021) This repository provides the code and data of the work in ACL20
PaSST: Efficient Training of Audio Transformers with Patchout
PaSST: Efficient Training of Audio Transformers with Patchout This is the implementation for Efficient Training of Audio Transformers with Patchout Pa
Multi-angle c(q)uestion answering
Macaw Introduction Macaw (Multi-angle c(q)uestion answering) is a ready-to-use model capable of general question answering, showing robustness outside
PyMultiDictionary is a Dictionary Module for Python 3+ to get meanings, translations, synonyms and antonyms of words in 20 different languages
PyMultiDictionary PyMultiDictionary is a Dictionary Module for Python 3+ to get meanings, translations, synonyms and antonyms of words in 20 different
Scalable training for dense retrieval models.
Scalable implementation of dense retrieval. Training on cluster By default it trains locally: PYTHONPATH=.:$PYTHONPATH python dpr_scale/main.py traine
NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in production.
NVIDIA Merlin NVIDIA Merlin is an open source library designed to accelerate recommender systems on NVIDIA’s GPUs. It enables data scientists, machine
The official code for PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization
PRIMER The official code for PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization. PRIMER is a pre-trained model for mu
MG-GCN: Scalable Multi-GPU GCN Training Framework
MG-GCN MG-GCN: multi-GPU GCN training framework. For more information, please read our paper. After cloning our repository, run git submodule update -
Official implementation of deep-multi-trajectory-based single object tracking (IEEE T-CSVT 2021).
DeepMTA_PyTorch Officical PyTorch Implementation of "Dynamic Attention-guided Multi-TrajectoryAnalysis for Single Object Tracking", Xiao Wang, Zhe Che
Demystifying How Self-Supervised Features Improve Training from Noisy Labels
Demystifying How Self-Supervised Features Improve Training from Noisy Labels This code is a PyTorch implementation of the paper "[Demystifying How Sel
Multi-Objective Loss Balancing for Physics-Informed Deep Learning
Multi-Objective Loss Balancing for Physics-Informed Deep Learning Code for ReLoBRaLo. Abstract Physics Informed Neural Networks (PINN) are algorithms
Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System
Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System Authors: Yixuan Su, Lei Shu, Elman Mansimov, Arshit Gupta, Deng Cai, Yi-An Lai
Source code for "Taming Visually Guided Sound Generation" (Oral at the BMVC 2021)
Taming Visually Guided Sound Generation • [Project Page] • [ArXiv] • [Poster] • • Listen for the samples on our project page. Overview We propose to t