1198 Repositories
Python self-training Libraries
This is the paddle code for SeBoW(Self-Born wiring for neural trees), a kind of neural tree born form a large search space
SeBoW: Self-Born Wiring for neural trees(PaddlePaddle version) This is the paddle code for SeBoW(Self-Born wiring for neural trees), a kind of neural
Tensorflow 2 implementations of the C-SimCLR and C-BYOL self-supervised visual representation methods from "Compressive Visual Representations" (NeurIPS 2021)
Compressive Visual Representations This repository contains the source code for our paper, Compressive Visual Representations. We developed informatio
VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning
VarCLR: Variable Representation Pre-training via Contrastive Learning New: Paper accepted by ICSE 2022. Preprint at arXiv! This repository contain
iBOT: Image BERT Pre-Training with Online Tokenizer
Image BERT Pre-Training with iBOT Official PyTorch implementation and pretrained models for paper iBOT: Image BERT Pre-Training with Online Tokenizer.
Code for CVPR2019 paper《Unequal Training for Deep Face Recognition with Long Tailed Noisy Data》
Unequal-Training-for-Deep-Face-Recognition-with-Long-Tailed-Noisy-Data. This is the code of CVPR 2019 paper《Unequal Training for Deep Face Recognition
Code for "Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification", ECCV 2020 Spotlight
Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification Implementation of "Learning From Multiple Experts: Se
[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning
Rethinking the Value of Labels for Improving Class-Imbalanced Learning This repository contains the implementation code for paper: Rethinking the Valu
Conceptual 12M is a dataset containing (image-URL, caption) pairs collected for vision-and-language pre-training.
Conceptual 12M We introduce the Conceptual 12M (CC12M), a dataset with ~12 million image-text pairs meant to be used for vision-and-language pre-train
Repo for CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning
CReST in Tensorflow 2 Code for the paper: "CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning" by Chen Wei, Ki
Uni-Fold: Training your own deep protein-folding models.
Uni-Fold: Training your own deep protein-folding models. This package provides and implementation of a trainable, Transformer-based deep protein foldi
Torchrecipes provides a set of reproduci-able, re-usable, ready-to-run RECIPES for training different types of models, across multiple domains, on PyTorch Lightning.
Recipes are a standard, well supported set of blueprints for machine learning engineers to rapidly train models using the latest research techniques without significant engineering overhead.Specifically, recipes aims to provide- Consistent access to pre-trained SOTA models ready for production- Reference implementations for SOTA research reproducibility, and infrastructure to guarantee correctness, efficiency, and interoperability.
iBOT: Image BERT Pre-Training with Online Tokenizer
Image BERT Pre-Training with iBOT Official PyTorch implementation and pretrained models for paper iBOT: Image BERT Pre-Training with Online Tokenizer.
SimMIM: A Simple Framework for Masked Image Modeling
SimMIM By Zhenda Xie*, Zheng Zhang*, Yue Cao*, Yutong Lin, Jianmin Bao, Zhuliang Yao, Qi Dai and Han Hu*. This repo is the official implementation of
An end to end ASR Transformer model training repo
END TO END ASR TRANSFORMER 本项目基于transformer 6*encoder+6*decoder的基本结构构造的端到端的语音识别系统 Model Instructions 1.数据准备: 自行下载数据,遵循文件结构如下: ├── data │ ├── train │
Training code for Korean multi-class sentiment analysis
KoSentimentAnalysis Bert implementation for the Korean multi-class sentiment analysis 왜 한국어 감정 다중분류 모델은 거의 없는 것일까?에서 시작된 프로젝트 Environment: Pytorch, Da
This repository is an implementation of paper : Improving the Training of Graph Neural Networks with Consistency Regularization
CRGNN Paper : Improving the Training of Graph Neural Networks with Consistency Regularization Environments Implementing environment: GeForce RTX™ 3090
GLIP: Grounded Language-Image Pre-training
GLIP: Grounded Language-Image Pre-training Updates 12/06/2021: GLIP paper on arxiv https://arxiv.org/abs/2112.03857. Code and Model are under internal
The best solution of the Weather Prediction track in the Yandex Shifts challenge
yandex-shifts-weather The repository contains information about my solution for the Weather Prediction track in the Yandex Shifts challenge https://re
This is an official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Recognition" in AAAI2022.
AimCLR This is an official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Reco
[AAAI2022] Source code for our paper《Suppressing Static Visual Cues via Normalizing Flows for Self-Supervised Video Representation Learning》
SSVC The source code for paper [Suppressing Static Visual Cues via Normalizing Flows for Self-Supervised Video Representation Learning] samples of the
This repository is an implementation of paper : Improving the Training of Graph Neural Networks with Consistency Regularization
CRGNN Paper : Improving the Training of Graph Neural Networks with Consistency Regularization Environments Implementing environment: GeForce RTX™ 3090
Post-Training Quantization for Vision transformers.
PTQ4ViT Post-Training Quantization Framework for Vision Transformers. We use the twin uniform quantization method to reduce the quantization error on
Self-Supervised Learning of Event-based Optical Flow with Spiking Neural Networks
Self-Supervised Learning of Event-based Optical Flow with Spiking Neural Networks Work accepted at NeurIPS'21 [paper, video]. If you use this code in
Robust Lane Detection via Expanded Self Attention (WACV 2022)
Robust Lane Detection via Expanded Self Attention (WACV 2022) Minhyeok Lee, Junhyeop Lee, Dogyoon Lee, Woojin Kim, Sangwon Hwang, Sangyoun Lee Overvie
Uni-Fold: Training your own deep protein-folding models
Uni-Fold: Training your own deep protein-folding models. This package provides an implementation of a trainable, Transformer-based deep protein foldin
Perturbed Self-Distillation: Weakly Supervised Large-Scale Point Cloud Semantic Segmentation (ICCV2021)
Perturbed Self-Distillation: Weakly Supervised Large-Scale Point Cloud Semantic Segmentation (ICCV2021) This is the implementation of PSD (ICCV 2021),
The easiest tool for extracting radiomics features and training ML models on them.
Simple pipeline for experimenting with radiomics features Installation git clone https://github.com/piotrekwoznicki/ClassyRadiomics.git cd classrad pi
Official Pytorch Implementation of Relational Self-Attention: What's Missing in Attention for Video Understanding
Relational Self-Attention: What's Missing in Attention for Video Understanding This repository is the official implementation of "Relational Self-Atte
Training Structured Neural Networks Through Manifold Identification and Variance Reduction
Training Structured Neural Networks Through Manifold Identification and Variance Reduction This repository is a pytorch implementation of the Regulari
VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning
VarCLR: Variable Representation Pre-training via Contrastive Learning New: Paper accepted by ICSE 2022. Preprint at arXiv! This repository contain
An official source code for "Augmentation-Free Self-Supervised Learning on Graphs"
Augmentation-Free Self-Supervised Learning on Graphs An official source code for Augmentation-Free Self-Supervised Learning on Graphs paper, accepted
Official repository for Automated Learning Rate Scheduler for Large-Batch Training (8th ICML Workshop on AutoML)
Automated Learning Rate Scheduler for Large-Batch Training The official repository for Automated Learning Rate Scheduler for Large-Batch Training (8th
An official source code for "Augmentation-Free Self-Supervised Learning on Graphs"
Augmentation-Free Self-Supervised Learning on Graphs An official source code for Augmentation-Free Self-Supervised Learning on Graphs paper, accepted
Self-adjusting, auto-compounding multi-pair DCA crypto trading bot using Python, AWS Lambda & 3Commas API
Self-adjusting, auto-compounding multi-pair DCA crypto trading bot using Python, AWS Lambda & 3Commas API The following code describes how we can leve
An OpenAI-Gym Package for Training and Testing Reinforcement Learning algorithms with OpenSim Models
Authors: Utkarsh A. Mishra and Dr. Dimitar Stanev Advisors: Dr. Dimitar Stanev and Prof. Auke Ijspeert, Biorobotics Laboratory (BioRob), EPFL Video Pl
PyTorch Implementation of Daft-Exprt: Robust Prosody Transfer Across Speakers for Expressive Speech Synthesis
PyTorch Implementation of Daft-Exprt: Robust Prosody Transfer Across Speakers for Expressive Speech Synthesis
FedTorch is an open-source Python package for distributed and federated training of machine learning models using PyTorch distributed API
FedTorch is a generic repository for benchmarking different federated and distributed learning algorithms using PyTorch Distributed API.
Yas CRNN model training - Yet Another Genshin Impact Scanner
Yas-Train Yet Another Genshin Impact Scanner 又一个原神圣遗物导出器 介绍 该仓库为 Yas 的模型训练程序 相关资料 MobileNetV3 CRNN 使用 假设你会设置基本的pytorch环境。 生成数据集 python main.py gen 训练
FuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space OptimizationFuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space Optimization
FuseDream This repo contains code for our paper (paper link): FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimizat
Reinforcement learning for self-driving in a 3D simulation
SelfDrive_AI Reinforcement learning for self-driving in a 3D simulation (Created using UNITY-3D) 1. Requirements for the SelfDrive_AI Gym You need Pyt
The Pytorch implementation for "Video-Text Pre-training with Learned Regions"
Region_Learner The Pytorch implementation for "Video-Text Pre-training with Learned Regions" (arxiv) We are still cleaning up the code further and pre
InsCLR: Improving Instance Retrieval with Self-Supervision
InsCLR: Improving Instance Retrieval with Self-Supervision This is an official PyTorch implementation of the InsCLR paper. Download Dataset Dataset Im
Official PyTorch implementation of our AAAI22 paper: TransMEF: A Transformer-Based Multi-Exposure Image Fusion Framework via Self-Supervised Multi-Task Learning. Code will be available soon.
Official-PyTorch-Implementation-of-TransMEF Official PyTorch implementation of our AAAI22 paper: TransMEF: A Transformer-Based Multi-Exposure Image Fu
Adaptive Denoising Training (ADT) for Recommendation.
DenoisingRec Adaptive Denoising Training for Recommendation. This is the pytorch implementation of our paper at WSDM 2021: Denoising Implicit Feedback
[NeurIPS 2021] ORL: Unsupervised Object-Level Representation Learning from Scene Images
Unsupervised Object-Level Representation Learning from Scene Images This repository contains the official PyTorch implementation of the ORL algorithm
Official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Recognition" in AAAI2022.
AimCLR This is an official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Reco
Code repository for "Reducing Underflow in Mixed Precision Training by Gradient Scaling" presented at IJCAI '20
Reducing Underflow in Mixed Precision Training by Gradient Scaling This project implements the gradient scaling method to improve the performance of m
Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation
Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation This repository contains the Pytorch implementation of the proposed
Rainbow DQN implementation accompanying the paper "Fast and Data-Efficient Training of Rainbow" which reaches 205.7 median HNS after 10M frames. 🌈
Rainbow 🌈 An implementation of Rainbow DQN which reaches a median HNS of 205.7 after only 10M frames (the original Rainbow from Hessel et al. 2017 re
Code for EMNLP 2021 paper: "Learning Implicit Sentiment in Aspect-based Sentiment Analysis with Supervised Contrastive Pre-Training"
SCAPT-ABSA Code for EMNLP2021 paper: "Learning Implicit Sentiment in Aspect-based Sentiment Analysis with Supervised Contrastive Pre-Training" Overvie
TextWorld is a sandbox learning environment for the training and evaluation of reinforcement learning (RL) agents on text-based games.
TextWorld A text-based game generator and extensible sandbox learning environment for training and testing reinforcement learning (RL) agents. Also ch
CLIP (Contrastive Language–Image Pre-training) trained on Indonesian data
CLIP-Indonesian CLIP (Radford et al., 2021) is a multimodal model that can connect images and text by training a vision encoder and a text encoder joi
Pipeline for training LSA models using Scikit-Learn.
Latent Semantic Analysis Pipeline for training LSA models using Scikit-Learn. Usage Instead of writing custom code for latent semantic analysis, you j
Monochrome's API, implemented with Deta Base and Deta Drive.
Monochrome Monochrome's API, implemented with Deta Base and Deta Drive. Create a free account on Deta to test this out! Most users will prefer the Mon
Pre-Training with Whole Word Masking for Chinese BERT
Pre-Training with Whole Word Masking for Chinese BERT
Official implementations for various pre-training models of ERNIE-family, covering topics of Language Understanding & Generation, Multimodal Understanding & Generation, and beyond.
English|简体中文 ERNIE是百度开创性提出的基于知识增强的持续学习语义理解框架,该框架将大数据预训练与多源丰富知识相结合,通过持续学习技术,不断吸收海量文本数据中词汇、结构、语义等方面的知识,实现模型效果不断进化。ERNIE在累积 40 余个典型 NLP 任务取得 SOTA 效果,并在 G
MPNet: Masked and Permuted Pre-training for Language Understanding
MPNet MPNet: Masked and Permuted Pre-training for Language Understanding, by Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, Tie-Yan Liu, is a novel pre-tr
(ACL-IJCNLP 2021) Convolutions and Self-Attention: Re-interpreting Relative Positions in Pre-trained Language Models.
BERT Convolutions Code for the paper Convolutions and Self-Attention: Re-interpreting Relative Positions in Pre-trained Language Models. Contains expe
Code for ICLR 2020 paper "VL-BERT: Pre-training of Generic Visual-Linguistic Representations".
VL-BERT By Weijie Su, Xizhou Zhu, Yue Cao, Bin Li, Lewei Lu, Furu Wei, Jifeng Dai. This repository is an official implementation of the paper VL-BERT:
Vision-Language Pre-training for Image Captioning and Question Answering
VLP This repo hosts the source code for our AAAI2020 work Vision-Language Pre-training (VLP). We have released the pre-trained model on Conceptual Cap
Research code for ECCV 2020 paper "UNITER: UNiversal Image-TExt Representation Learning"
UNITER: UNiversal Image-TExt Representation Learning This is the official repository of UNITER (ECCV 2020). This repository currently supports finetun
Oscar and VinVL
Oscar: Object-Semantics Aligned Pre-training for Vision-and-Language Tasks VinVL: Revisiting Visual Representations in Vision-Language Models Updates
Research Code for NeurIPS 2020 Spotlight paper "Large-Scale Adversarial Training for Vision-and-Language Representation Learning": UNITER adversarial training part
VILLA: Vision-and-Language Adversarial Training This is the official repository of VILLA (NeurIPS 2020 Spotlight). This repository currently supports
A Fast Knowledge Distillation Framework for Visual Recognition
FKD: A Fast Knowledge Distillation Framework for Visual Recognition Official PyTorch implementation of paper A Fast Knowledge Distillation Framework f
Codebase for Inducing Causal Structure for Interpretable Neural Networks
Interchange Intervention Training (IIT) Codebase for Inducing Causal Structure for Interpretable Neural Networks Release Notes 12/01/2021: Code and Pa
A PyTorch Toolbox for Face Recognition
FaceX-Zoo FaceX-Zoo is a PyTorch toolbox for face recognition. It provides a training module with various supervisory heads and backbones towards stat
A fast, pure python implementation of the MuyGPs Gaussian process realization and training algorithm.
Fast implementation of the MuyGPs Gaussian process hyperparameter estimation algorithm MuyGPs is a GP estimation method that affords fast hyperparamet
Graph Self-Attention Network for Learning Spatial-Temporal Interaction Representation in Autonomous Driving
GSAN Introduction Code for paper GSAN: Graph Self-Attention Network for Learning Spatial-Temporal Interaction Representation in Autonomous Driving, wh
Self-Supervised Learning with Kernel Dependence Maximization
Self-Supervised Learning with Kernel Dependence Maximization This is the code for SSL-HSIC, a self-supervised learning loss proposed in the paper Self
PyTorch implementation of paper A Fast Knowledge Distillation Framework for Visual Recognition.
FKD: A Fast Knowledge Distillation Framework for Visual Recognition Official PyTorch implementation of paper A Fast Knowledge Distillation Framework f
A simple framwork to streamline the Domain Adaptation training process.
FastDA Introduction This is a simple framework for domain adaptation training. You can use it to build your own training process. It heavily relies on
Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks
Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks Contributions A novel pairwise feature LSP to extract structural
A light weight data augmentation tool for training CNNs and Viola Jones detectors
hey-daug A light weight data augmentation tool for training CNNs and Viola Jones detectors (Haar Cascades). This tool inflates your data by up to six
Tools for curating biomedical training data for large-scale language modeling
Tools for curating biomedical training data for large-scale language modeling
Code for this paper The Lottery Ticket Hypothesis for Pre-trained BERT Networks.
The Lottery Ticket Hypothesis for Pre-trained BERT Networks Code for this paper The Lottery Ticket Hypothesis for Pre-trained BERT Networks. [NeurIPS
Source code for "Efficient Training of BERT by Progressively Stacking"
Introduction This repository is the code to reproduce the result of Efficient Training of BERT by Progressively Stacking. The code is based on Fairseq
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
ELECTRA Introduction ELECTRA is a method for self-supervised language representation learning. It can be used to pre-train transformer networks using
Understanding the Difficulty of Training Transformers
Admin Understanding the Difficulty of Training Transformers Guided by our analyses, we propose Adaptive Model Initialization (Admin), which successful
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
DeepSpeed+Megatron trained the world's most powerful language model: MT-530B DeepSpeed is hiring, come join us! DeepSpeed is a deep learning optimizat
[ACL-IJCNLP 2021] "EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets"
EarlyBERT This is the official implementation for the paper in ACL-IJCNLP 2021 "EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets" by
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
ALBERT ***************New March 28, 2020 *************** Add a colab tutorial to run fine-tuning for GLUE datasets. ***************New January 7, 2020
Source code for "FastBERT: a Self-distilling BERT with Adaptive Inference Time".
FastBERT Source code for "FastBERT: a Self-distilling BERT with Adaptive Inference Time". Good News 2021/10/29 - Code: Code of FastPLM is released on
Training and evaluation codes for the BertGen paper (ACL-IJCNLP 2021)
BERTGEN This repository is the implementation of the paper "BERTGEN: Multi-task Generation through BERT" (https://arxiv.org/abs/2106.03484). The codeb
Revisiting Self-Training for Few-Shot Learning of Language Model.
SFLM This is the implementation of the paper Revisiting Self-Training for Few-Shot Learning of Language Model. SFLM is short for self-training for few
[EMNLP 2021] Improving and Simplifying Pattern Exploiting Training
ADAPET This repository contains the official code for the paper: "Improving and Simplifying Pattern Exploiting Training". The model improves and simpl
The code is the training example of AAAI2022 Security AI Challenger Program Phase 8: Data Centric Robot Learning on ML models.
Example code of [Tianchi AAAI2022 Security AI Challenger Program Phase 8]
Python bilgilerimi eğlenceli bir şekilde hatırlamak ve daha da geliştirmek için The Big Book of Small Python Projects isimli bir kitap almıştım.
Python bilgilerimi eğlenceli bir şekilde hatırlamak ve daha da geliştirmek için The Big Book of Small Python Projects isimli bir kitap almıştım. Bu repo kitaptaki örnek programları çalıştığım oyun alanım.
Cooperative Driving Dataset: a dataset for multi-agent driving scenarios
Cooperative Driving Dataset (CODD) The Cooperative Driving dataset is a synthetic dataset generated using CARLA that contains lidar data from multiple
Self-Supervised Pre-Training for Transformer-Based Person Re-Identification
Self-Supervised Pre-Training for Transformer-Based Person Re-Identification [pdf] The official repository for Self-Supervised Pre-Training for Transfo
Efficient training of deep recommenders on cloud.
HybridBackend Introduction HybridBackend is a training framework for deep recommenders which bridges the gap between evolving cloud infrastructure and
Official implementation of the method ContIG, for self-supervised learning from medical imaging with genomics
ContIG: Self-supervised Multimodal Contrastive Learning for Medical Imaging with Genetics This is the code implementation of the paper "ContIG: Self-s
An official PyTorch implementation of the TKDE paper "Self-Supervised Graph Representation Learning via Topology Transformations".
Self-Supervised Graph Representation Learning via Topology Transformations This repository is the official PyTorch implementation of the following pap
Official Implementation of DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation
DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation [Arxiv] [Paper] As acquiring pixel-wise an
Code for "Adversarial Training for a Hybrid Approach to Aspect-Based Sentiment Analysis
HAABSAStar Code for "Adversarial Training for a Hybrid Approach to Aspect-Based Sentiment Analysis". This project builds on the code from https://gith
Self-Supervised Image Denoising via Iterative Data Refinement
Self-Supervised Image Denoising via Iterative Data Refinement Yi Zhang1, Dasong Li1, Ka Lung Law2, Xiaogang Wang1, Hongwei Qin2, Hongsheng Li1 1CUHK-S
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
[NeurIPS 2021] Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples | ⛰️⚠️
Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples This repository is the official implementation of "Tow
Official implementation of the NeurIPS 2021 paper Online Learning Of Neural Computations From Sparse Temporal Feedback
Online Learning Of Neural Computations From Sparse Temporal Feedback This repository is the official implementation of the NeurIPS 2021 paper Online L
Official implementation for TTT++: When Does Self-supervised Test-time Training Fail or Thrive
TTT++ This is an official implementation for TTT++: When Does Self-supervised Test-time Training Fail or Thrive? TL;DR: Online Feature Alignment + Str
[NIPS 2021] UOTA: Improving Self-supervised Learning with Automated Unsupervised Outlier Arbitration.
UOTA: Improving Self-supervised Learning with Automated Unsupervised Outlier Arbitration This repository is the official PyTorch implementation of UOT