Python Self-training Resources

Status: Archive (code is provided as-is, no updates expected) improved-gan code for the paper "Improved Techniques for Training GANs" MNIST, SVHN, CIF

Self Organising Map for Clustering of Atomistic Samples - V2 Description Self Organising Map (also known as Kohonen Network) implemented in Python for

What's New Below we share, in reverse chronological order, the updates and new releases in VISSL. All VISSL releases are available here. [Oct 2021]: V

MiniSom Self Organizing Maps MiniSom is a minimalistic and Numpy based implementation of the Self Organizing Maps (SOM). SOM is a type of Artificial N

JBHI-Pytorch This repository contains a reference implementation of the algorithms described in our paper "Self-supervised Multi-modal Hybrid Fusion N

High performance distributed framework for training deep learning recommendation models based on PyTorch.

CCQA: A New Web-Scale Question Answering Dataset for Model Pre-Training This is the official repository for the code and models of the paper CCQA: A N

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

self-supervised-landmarks Repository for self-supervised landmark discovery Requirements pytorch pynrrd (for 3d images) Usage The use of this models i

Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization This repository contains the source code for the paper (link wi

Robust and Accurate Object Detection via Self-Knowledge Distillation paper:https://arxiv.org/abs/2111.07239 Environments Python 3.7 Cuda 10.1 Prepare

LHC-Net Local Multi-Head Channel Self-Attention This repository is intended to provide a quick implementation of the LHC-Net and to replicate the resu

RobustBioNLP Improving the robustness and performance of biomedical NLP models through adversarial training In this repository you can find suppliment

TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Authors: Yixuan Su, Fangyu Liu, Zaiqiao Meng, Lei Shu, Ehsan Shareghi, and Nig

SASE : Self-Adaptive noise distribution network for Speech Enhancement with heterogeneous data of Cross-Silo Federated learning We propose a SASE mode

AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet buil

Alpha Zero General (any game, any framework!) A simplified, highly flexible, commented and (hopefully) easy to understand implementation of self-play

Donkeycar is minimalist and modular self driving library for Python. It is developed for hobbyists and students with a focus on allowing fast experimentation and easy community contributions.

Knock Knock A small library to get a notification when your training is complete or when it crashes during the process with two additional lines of co

CCNet: Criss-Cross Attention for Semantic Segmentation Paper Links: Our most recent TPAMI version with improvements and extensions (Earlier ICCV versi

TorchSeg This project aims at providing a fast, modular reference implementation for semantic segmentation models using PyTorch. Highlights Modular De

Training Reproduce of PSPNet. (Updated 2021/04/09. Authors of PSPNet have provided a Pytorch implementation for PSPNet and their new work with support

ERFNet This code is a toolbox that uses Torch library for training and evaluating the ERFNet architecture for semantic segmentation. NEW!! New PyTorch

ENet This work has been published in arXiv: ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. Packages: train contains too

fcn - Fully Convolutional Networks Chainer implementation of Fully Convolutional Networks. Installation pip install fcn Inference Inference is done as

G2S This is the official code for ICRA 2021 Paper: Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimation by Hemang

Training BERT with Compute/Time (Academic) Budget This repository contains scripts for pre-training and finetuning BERT-like models with limited time

Full-Body Visual Self-Modeling of Robot Morphologies Boyuan Chen, Robert Kwiatkowskig, Carl Vondrick, Hod Lipson Columbia University Project Website |

ucheck Automate UCheck COVID-19 self-assessment form submission. Disclaimer ucheck automatically completes the University of Tornto's UCheck COVID-19

Movenet.Pytorch Intro MoveNet is an ultra fast and accurate model that detects 17 keypoints of a body. This is A Pytorch implementation of MoveNet fro

Template Script Category Description Category script comparison script train.py, loader.py for single-machine-multiple-cards training train_DP.py, tra

The example shows using local self-hosted runners on-premises by making use of a runner on a Raspberry Pi with LED's attached to it

SAT: 2D Semantics Assisted Training for 3D Visual Grounding SAT: 2D Semantics Assisted Training for 3D Visual Grounding by Zhengyuan Yang, Songyang Zh

Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style [NeurIPS 2021] Official code to reproduce the results and data p

yolov5-helmet-detection-python A Python implementation of Yolov5 to detect head or helmet in the wild in Jetson Xavier nx and Jetson nano. In Jetson X

MQBench Quantization Aware Training with PyTorch I am using MQBench(Model Quantization Benchmark)(http://mqbench.tech/) to quantize the model for depl

MQBench Quantization Aware Training with PyTorch I am using MQBench(Model Quantization Benchmark)(http://mqbench.tech/) to quantize the model for depl

WitheredBot A Discord Self bot written in python Requirement Python = 3.9 How to Configure git clone https://github.com/a-a-a-aa/WitheredBot.git cd W

Official Code Release for "TIP-Adapter: Training-free clIP-Adapter for Better Vision-Language Modeling" Pipeline of Tip-Adapter Tip-Adapter can provid

TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Authors: Yixuan Su, Fangyu Liu, Zaiqiao Meng, Lei Shu, Ehsan Shareghi, and Nig

EquivariantSelfAttention An implementation of Equivariant e2 convolutional kernals into a convolutional self attention network, applied to radio astro

Overview This repository provides the implementation for the paper "Improved Regularization and Robustness for Fine-tuning in Neural Networks", which

Introduction Official implementation of "Membership Inference Attacks Against Self-supervised Speech Models". In this work, we demonstrate that existi

Self-Supervised Collision Handling via Generative 3D Garment Models for Virtual Try-On [Project website] [Dataset] [Video] Abstract We propose a new g

TaCL: Improve BERT Pre-training with Token-aware Contrastive Learning

Training-Curve-Vis Visualize the training curve from the *.csv file (tensorboard format). Feature Custom labels Curve smoothing Support for multiple c

Just Ask: Learning to Answer Questions from Millions of Narrated Videos Webpage • Demo • Paper This repository provides the code for our paper, includ

ADDS-DepthNet This is the official implementation of the paper Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation I

OcCo: Unsupervised Point Cloud Pre-training via Occlusion Completion This repository is the official implementation of paper: "Unsupervised Point Clou

DeT and DOT Code and datasets for "DepthTrack: Unveiling the Power of RGBD Tracking" (ICCV2021) "Depth-only Object Tracking" (BMVC2021) @InProceedings

MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Driving Code will be available soon. Motivation Architecture

Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet, ICCV 2021 Update: 2021/03/11: update our new results. Now our T2T-ViT-14 w

W.I.P-Aim-Memory-Game A customisable game where you have to quickly click on black tiles in order of appearance while avoiding clicking on white squar

PaSST: Efficient Training of Audio Transformers with Patchout This is the implementation for Efficient Training of Audio Transformers with Patchout Pa

LiST (Lite Self-Training) This is the implementation of the paper LiST: Lite Self-training Makes Efficient Few-shot Learners. LiST is short for Lite S

How to use Double click avery.exe, and follow the prompts Features Important! Make sure to use [9] (Scrape Info) before using these, or some things ma

LibreTranslate Try it online! | API Docs | Community Forum Free and Open Source Machine Translation API, entirely self-hosted. Unlike other APIs, it d

Skyformer This repository is the official implementation of Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr"om Method (NeurIPS 2021).

Self-supervised Product Quantization for Deep Unsupervised Image Retrieval Pytorch implementation of SPQ Accepted to ICCV 2021 - paper Young Kyun Jang

What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments? [Paper] [ICML'21 Project] PyTorch Implementation T

A Simple Framwork for CV Pre-training Model (SOCO, VirTex, BEiT)

Efficient Sharpness-aware Minimization for Improved Training of Neural Networks Code for “Efficient Sharpness-aware Minimization for Improved Training

VoCapXLM Code for EMNLP2021 paper Allocating Large Vocabulary Capacity for Cross-lingual Language Model Pre-training Environment DockerFile: dancingso

CFN-SR A CROSS-MODAL FUSION NETWORK BASED ON SELF-ATTENTION AND RESIDUAL STRUCTURE FOR MULTIMODAL EMOTION RECOGNITION The audio-video based multimodal

Who's there? The spiritual successor to knockknock for PyTorch Lightning, to get a notification when your training is complete or when it crashes duri

Skyformer This repository is the official implementation of Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr"om Method (NeurIPS 2021).

Revealing and Protecting Labels in Distributed Training

FastCover: A Self-Supervised Learning Framework for Multi-Hop Influence Maximization in Social Networks by Anonymous.

Structure Information is the Key: Self-Attention RoI Feature Extractor in 3D Object Detection abstract:Unlike 2D object detection where all RoI featur

Trainig Script for Space Time Memory Network This codebase implemented training code for Space Time Memory Network with some cyclic features. Requirem

Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (Local-Lip) Introduction TL;DR: We propose an efficient and trainabl

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

Contrastive Self-Supervised Learning on CIFAR-10 Paper "Towards the Generalization of Contrastive Self-Supervised Learning", Weiran Huang, Mingyang Yi

Your self-hosted bookmark archive. Free and open source. Contents About LinkAce Support Setup Contribution About LinkAce LinkAce is a self-hosted arch

LOCKER This is the pytorch implementation of this paper: Locally Constrained Self-Attentive Sequential Recommendation. Zhankui He, Handong Zhao, Zhe L

Enhancing Knowledge Tracing via Adversarial Training This repository contains source code for the paper "Enhancing Knowledge Tracing via Adversarial T

Training Deep Learning Models on The Edge Training on the Edge enables continuous learning from new data for deployed neural networks on memory-constr

Lossy Compression for Lossless Prediction Using: Training: This repostiory contains our implementation of the paper: Lossy Compression for Lossless Pr

Relating Adversarially Robust Generalization to Flat Minima This repository contains code corresponding to the MLSys'21 paper: D. Stutz, M. Hein, B. S

Machine Learning Portal Goal Application Workflow Process Design Live Project Goal A complete end-to-end machine learning portal that covers processes

Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)

Code for Coordinated Policy Optimization Webpage | Code | Paper | Talk (English) | Talk (Chinese) Hi there! This is the source code of the paper “Lear

Deep-FIR Codebase - Super Resolution Meta Attention Networks About This repository contains the main coding framework accompanying our work on meta-at

Intermdiate layer matters - SSL The official repository for "Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning" paper. Downl

1. SaWDE.m is the main function 2. DataPartition.m is used to randomly partition the original data into training sets and test sets with a ratio of 7

Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks Setup This implementation is based on PyTorch = 1.0.0. Smal

IP-IRM [NeurIPS 2021] The PyTorch implementation of paper "Self-Supervised Learning Disentangled Group Representation as Feature". Codes will be relea

ColossalAI An integrated large-scale model training system with efficient parallelization techniques. arXiv: Colossal-AI: A Unified Deep Learning Syst

Package Delivery Rover 🚀 This project is a prototype of Self Driving Car. It's based on embedded systems, to meet the current requirement of delivery

PubTables-1M This repository contains training and evaluation code for the paper "PubTables-1M: Towards a universal dataset and metrics for training a

Predicting lncRNA–protein interactions based on graph autoencoders and collaborative training Code for our paper "Predicting lncRNA–protein interactio

ColossalAI An integrated large-scale model training system with efficient parallelization techniques Installation PyPI pip install colossalai Install

[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.

Exponential Graph is Provably Efficient for Decentralized Deep Training This code repository is for the paper Exponential Graph is Provably Efficient

AugMax: Adversarial Composition of Random Augmentations for Robust Training Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Anima Anandkumar, an

CSA: Contextual Similarity Aggregation with Self-attention for Visual Re-ranking PyTorch training code for CSA (Contextual Similarity Aggregation). We

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

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

A Simple Baseline for Low-Budget Active Learning This repository is the implementation of A Simple Baseline for Low-Budget Active Learning. In this pa

Asterisk is a framework to generate high-quality training datasets at scale