Python Self-training-ensembles Resources

Self-Supervised Image Denoising via Iterative Data Refinement Yi Zhang1, Dasong Li1, Ka Lung Law2, Xiaogang Wang1, Hongwei Qin2, Hongsheng Li1 1CUHK-S

Shunted Transformer This is the offical implementation of Shunted Self-Attention via Multi-Scale Token Aggregation by Sucheng Ren, Daquan Zhou, Shengf

Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples This repository is the official implementation of "Tow

Online Learning Of Neural Computations From Sparse Temporal Feedback This repository is the official implementation of the NeurIPS 2021 paper Online L

TTT++ This is an official implementation for TTT++: When Does Self-supervised Test-time Training Fail or Thrive? TL;DR: Online Feature Alignment + Str

UOTA: Improving Self-supervised Learning with Automated Unsupervised Outlier Arbitration This repository is the official PyTorch implementation of UOT

PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models This repository is the official implementation of the fol

Large-scale pre-trained language models (PLMs) such as BERT and GPT have achieved great success and become a milestone in NLP.

Backbone for PyTorch training loop Will try to keep it minimalistic. pip install back from back import Bone Features Progress bar Checkpoints saving/l

Self-Supervised Bug Detection and Repair This is the reference code to replicate the research in Self-Supervised Bug Detection and Repair in NeurIPS 2

multi-task_losses_optimizer Implement the Pareto Optimizer and pcgrad to make a self-adaptive loss for multi-task 已经实验过了，不会有cuda out of memory情况 ##Par

Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data (NeurIPS 2021) This repository provides the official PyTorch implementation

Description Small wrapper around 3dmol.js and html2canvas for creating self-contained HTML files that display a 3D molecular representation. Double cl

CCOP Code of our paper Contrastive Object-level Pre-training with Spatial Noise Curriculum Learning Requirement Install OpenSelfSup Install Detectron2

FQ-ViT [arXiv] This repo contains the official implementation of "FQ-ViT: Fully Quantized Vision Transformer without Retraining". Table of Contents In

Saliency Guided Training Code implementing "Improving Deep Learning Interpretability by Saliency Guided Training" by Aya Abdelsalam Ismail, Hector Cor

Point-BERT: Pre-Training 3D Point Cloud Transformers with Masked Point Modeling Created by Xumin Yu*, Lulu Tang*, Yongming Rao*, Tiejun Huang, Jie Zho

League of Legends Reinforcement Learning Environment (LoLRLE) About This repo contains code to train an agent to play league of legends in a distribut

Few-shot Deep HDR Deghosting This repository contains code and pretrained models for our paper: Self-Gated Memory Recurrent Network for Efficient Scal

Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics. By Andres Milioto @ University of Bonn. (for the new P

pytorch-framework PyTorch common framework to accelerate network implementation, training and validation. This framework is inspired by works from MML

CCOP Code of our paper Contrastive Object-level Pre-training with Spatial Noise Curriculum Learning Requirement Install OpenSelfSup Install Detectron2

Subspace Adversarial Training Single-step adversarial training (AT) has received wide attention as it proved to be both efficient and robust. However,

Self Supervised clusterer Combined IIC, and Moco architectures, with some SimCLR notions, to get state of the art unsupervised clustering while retain

PyDiar This repo contains simple to use, pretrained/training-less models for speaker diarization. Supported Models Binary Key Speaker Modeling Based o

BlenderProc2 A procedural Blender pipeline for photorealistic rendering. Documentation | Tutorials | Examples | ArXiv paper | Workshop paper Features

Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks This repository contains the official code for the

Train Opus-MT models This package includes scripts for training NMT models using MarianNMT and OPUS data for OPUS-MT. More details are given in the Ma

PERSIA (Parallel rEcommendation tRaining System with hybrId Acceleration) is developed by AI platform@Kuaishou Technology, collaborating with ETH. It

LaneNet-Lane-Detection Use tensorflow to implement a Deep Neural Network for real time lane detection mainly based on the IEEE IV conference paper "To

Automatically download the cwru data set, and then divide it into training data set and test data set.自动下载cwru数据集，然后分训练数据集和测试数据集

clip-text-decoder Generate text captions for images from their CLIP embeddings. Includes PyTorch model code and example training script. Example Predi

private-transformers This codebase facilitates fast experimentation of differentially private training of Hugging Face transformers. What is this? Why

Pytorch library for end-to-end transformer models training and serving

Meta-Learning to Improve Pre-Training This folder contains code to run experiments in the paper Meta-Learning to Improve Pre-Training, NeurIPS 2021. P

Invitease Description A self contained invitation management system for gatekeeping. Purpose Serves as a focal point for inviting guests to a venue pr

PeCo: Perceptual Codebook for BERT Pre-training of Vision Transformers

This repository allows you to get started with training a state-of-the-art Deep Learning model with little to no configuration needed! You provide your labeled dataset or label your dataset using our BMW-LabelTool-Lite and you can start the training right away and monitor it in many different ways like TensorBoard or a custom REST API and GUI. NoCode training with YOLOv4 and YOLOV3 has never been so easy.

Intel(R) Extension for Scikit-learn* Installation | Documentation | Examples | Support | FAQ With Intel(R) Extension for Scikit-learn you can accelera

RTM3D-PyTorch The PyTorch Implementation of the paper: RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Driving (ECCV 2020

Bootstrap Your Own Latent (BYOL), in Pytorch Practical implementation of an astoundingly simple method for self-supervised learning that achieves a ne

Softlearning Softlearning is a deep reinforcement learning toolbox for training maximum entropy policies in continuous domains. The implementation is

Tic-Tac-Toe Nosso famoso e tradicional Jogo da Velha, mas agora em Python. Development setup Para rodar o programa, basta instalar python em sua maqui

Self-Supervised Policy Adaptation during Deployment PyTorch implementation of PAD and evaluation benchmarks from Self-Supervised Policy Adaptation dur

ADGC: Awesome Deep Graph Clustering ADGC is a collection of state-of-the-art (SOTA), novel deep graph clustering methods (papers, codes and datasets).

TiSASRec.paddle A PaddlePaddle implementation of Time Interval Aware Self-Attentive Sequential Recommendation. Introduction 论文：Time Interval Aware Sel

mass-dm-requests - Little preview of the Logger and the Spammer Features Logging User IDS Sending DMs (Embeds are supported) to the logged IDs Includi

Self-Regulated Learning for Egocentric Video Activity Anticipation Introduction This is a Pytorch implementation of the model described in our paper:

Pruning Self-attentions into Convolutional Layers in Single Path This is the official repository for our paper: Pruning Self-attentions into Convoluti

Self-Supervised Pre-Training for Transformer-Based Person Re-Identification [pdf] The official repository for Self-Supervised Pre-Training for Transfo

PSSL Source code of CIKM2021 Long Paper "PSSL: Self-supervised Learning for Personalized Search with Contrastive Sampling". It consists of the pre-tra

Stylegan2-Ada-Google-Colab-Starter-Notebook A no thrills colab notebook for training Stylegan2-ada on colab. transfer learning onto your own dataset h

Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations Code repo for paper Trans-Encoder: Unsupervised sentence-pa

Accelerated Sparse Neural Training: A Provable and Efficient Method to FindN:M Transposable Masks Recently, researchers proposed pruning deep neural n

DisCo: Remedy Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning Pytorch Implementation for DisCo: Remedy Self-supervi

Pruning Self-attentions into Convolutional Layers in Single Path This is the official repository for our paper: Pruning Self-attentions into Convoluti

SE(3)-eSCOPE video | paper | website Leveraging SE(3) Equivariance for Self-Supervised Category-Level Object Pose Estimation Xiaolong Li, Yijia Weng,

Masked Autoencoders Are Scalable Vision Learners A TensorFlow implementation of Masked Autoencoders Are Scalable Vision Learners [1]. Our implementati

Self-Supervised Document Similarity Ranking (SDR) via Contextualized Language Models and Hierarchical Inference This repo is the implementation for SD

Delve is a Python package for analyzing the inference dynamics of your PyTorch model.

Self Supervised Learning with Fastai Implementation of popular SOTA self-supervised learning algorithms as Fastai Callbacks. Install pip install self-

fast.ai ULMFiT with SentencePiece from pretraining to deployment Motivation: Why even bother with a non-BERT / Transformer language model? Short answe

Welcome to AdaptNLP A high level framework and library for running, training, and deploying state-of-the-art Natural Language Processing (NLP) models

An Agnostic Object Detection Framework IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-q

A Memory-saving Training Framework for Transformers This is the official PyTorch implementation for Mesa: A Memory-saving Training Framework for Trans

DABS: A Domain Agnostic Benchmark for Self-Supervised Learning This repository contains the code for DABS, a benchmark for domain-agnostic self-superv

Awesome Depth Completion Table of Contents About Sparse-to-Dense Depth Completion Current State of Depth Completion Unsupervised VOID Benchmark Superv

livelossplot Don't train deep learning models blindfolded! Be impatient and look at each epoch of your training! (RECENT CHANGES, EXAMPLES IN COLAB, A

InfiniteBoost Code for a paper InfiniteBoost: building infinite ensembles with gradient descent (arXiv:1706.01109). A. Rogozhnikov, T. Likhomanenko De

Distributed Arcface Training in Pytorch

Mesa: A Memory-saving Training Framework for Transformers This is the official PyTorch implementation for Mesa: A Memory-saving Training Framework for

Welcome to AirSim AirSim is a simulator for drones, cars and more, built on Unreal Engine (we now also have an experimental Unity release). It is open

Self-Supervised Monocular 3D Face Reconstruction by Occlusion-Aware Multi-view Geometry Consistency(ECCV 2020) This is an official python implementati

DSM The source code for paper Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion Project Website; Datasets li

The pure and clear PyTorch Distributed Training Framework. Introduction Requirements and Usage Dependency Dataset Basic Usage Slurm Cluster Usage Base

Factorisation-based Image Labelling Overview This is a scheme for training and applying the factorisation-based image labelling (FIL) framework. Some

YOLOv4 CrowdHuman Tutorial This is a tutorial demonstrating how to train a YOLOv4 people detector using Darknet and the CrowdHuman dataset. Table of c

Barlow-Twins-TF This repository implements Barlow Twins (Barlow Twins: Self-Supervised Learning via Redundancy Reduction) in TensorFlow and demonstrat

Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).

HiddenLayer A lightweight library for neural network graphs and training metrics for PyTorch, Tensorflow, and Keras. HiddenLayer is simple, easy to ex

SageMaker Python SDK SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. With the S

MIT Deep Learning This repository is a collection of tutorials for MIT Deep Learning courses. More added as courses progress. Tutorial: Deep Learning

In this repository, the code to use Udacity's self driving car simulator as a testbed for training an autonomous car are provided.

Automatic Parallel Parking: Path Planning, Path Tracking & Control This repository contains a python implementation of an automatic parallel parking s

Robust Self-augmentation for NER with Meta-reweighting

Badtray This is a very simple self-hosted server to receive files from remote systems. This works similar to Bintray (RIP) and primarily designed to d

SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness (NeurIPS2021) This repository contains code for the paper "Smo

Low Precision Decentralized Training with Heterogenous Data Official PyTorch implementation for "Low Precision Decentralized Distributed Training with

Improving Transferability of Representations via Augmentation-Aware Self-Supervision Accepted to NeurIPS 2021 TL;DR: Learning augmentation-aware infor

Fisher Induced Sparse uncHanging (FISH) Mask This repo contains the code for Fisher Induced Sparse uncHanging (FISH) Mask training, from "Training Neu

You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling Transformer-based models are widely used in natural language processi

English | 简体中文 Latest News 2021.10.25 Paper "Docking-based Virtual Screening with Multi-Task Learning" is accepted by BIBM 2021. 2021.07.29 PaddleHeli

DeBERTa: Decoding-enhanced BERT with Disentangled Attention This repository is the official implementation of DeBERTa: Decoding-enhanced BERT with Dis

SATGAN TODO: update the article URL once published. Article about this implemention The self-attentive task generative adversarial network (SATGAN) le

Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks This is a Pytorch-Lightning implementation of the paper "Self-s

Simulation Dataset for BBHnet NOTE: OLD README, UPDATE IN PROGRESS We generate simulation dataset to train BBHnet, our deep learning framework for det

AI Choreographer: Music Conditioned 3D Dance Generation with AIST++ [ICCV-2021]. Overview This package contains the model implementation and training

MAE for Self-supervised ViT Introduction This is an unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners for self-sup

Code for paper "Context-self contrastive pretraining for crop type semantic segmentation" Setting up a python environment Follow the instruction in ht

PyTorch Kafka Dataset: A definition of a dataset to get training data from Kafka.