1198 Repositories
Python self-training Libraries
The official implementation of the paper, "SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning"
SubTab: Author: Talip Ucar ([email protected]) The official implementation of the paper, SubTab: Subsetting Features of Tabular Data for Self-Supervis
Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR
Official implementation for paper "Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR"
Code for the paper Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph Representations (AKBC 2021).
Relation Prediction as an Auxiliary Training Objective for Knowledge Base Completion This repo provides the code for the paper Relation Prediction as
Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR
UniSpeech The family of UniSpeech: UniSpeech (ICML 2021): Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR UniSpeech-
Pre-training BERT masked language models with custom vocabulary
Pre-training BERT Masked Language Models (MLM) This repository contains the method to pre-train a BERT model using custom vocabulary. It was used to p
Video Autoencoder: self-supervised disentanglement of 3D structure and motion
Video Autoencoder: self-supervised disentanglement of 3D structure and motion This repository contains the code (in PyTorch) for the model introduced
A simple but useful Discord Selfbot with essential features, made with discord.py-self.
Discord Selfbot Xyno Discord Selfbot Xyno is a simple but useful selfbot for Discord. It has currently limited useful features but it will be updated
Unofficial PyTorch implementation of DeepMind's Perceiver IO with PyTorch Lightning scripts for distributed training
Unofficial PyTorch implementation of DeepMind's Perceiver IO with PyTorch Lightning scripts for distributed training
This is the official pytorch implementation of Student Helping Teacher: Teacher Evolution via Self-Knowledge Distillation(TESKD)
Student Helping Teacher: Teacher Evolution via Self-Knowledge Distillation (TESKD) By Zheng Li[1,4], Xiang Li[2], Lingfeng Yang[2,4], Jian Yang[2], Zh
ICLR 2021: Pre-Training for Context Representation in Conversational Semantic Parsing
SCoRe: Pre-Training for Context Representation in Conversational Semantic Parsing This repository contains code for the ICLR 2021 paper "SCoRE: Pre-Tr
Training vision models with full-batch gradient descent and regularization
Stochastic Training is Not Necessary for Generalization -- Training competitive vision models without stochasticity This repository implements trainin
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
deep-table implements various state-of-the-art deep learning and self-supervised learning algorithms for tabular data using PyTorch.
deep-table implements various state-of-the-art deep learning and self-supervised learning algorithms for tabular data using PyTorch.
spam_box is a self hosted temp mail service by hacksec
spam_box spam_box is a self hosted temp mail service by hacksec Requirement python3 open port 25 and 6660 root access in a vps How to install in linux
An official reimplementation of the method described in the INTERSPEECH 2021 paper - Speech Resynthesis from Discrete Disentangled Self-Supervised Representations.
Speech Resynthesis from Discrete Disentangled Self-Supervised Representations Implementation of the method described in the Speech Resynthesis from Di
A simple recipe for training and inferencing Transformer architecture for Multi-Task Learning on custom datasets. You can find two approaches for achieving this in this repo.
multitask-learning-transformers A simple recipe for training and inferencing Transformer architecture for Multi-Task Learning on custom datasets. You
[ICCV 2021] Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation
EPCDepth EPCDepth is a self-supervised monocular depth estimation model, whose supervision is coming from the other image in a stereo pair. Details ar
🧬 Training the car to do self-parking using a genetic algorithm
🧬 Training the car to do self-parking using a genetic algorithm
Model factory is a ML training platform to help engineers to build ML models at scale
Model Factory Machine learning today is powering many businesses today, e.g., search engine, e-commerce, news or feed recommendation. Training high qu
Self-Supervised depth kalilia
Self-Supervised depth kalilia
🔥🔥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
Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018
Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples This project is for the paper "Training Confidence-Calibrated Clas
NEATEST: Evolving Neural Networks Through Augmenting Topologies with Evolution Strategy Training
NEATEST: Evolving Neural Networks Through Augmenting Topologies with Evolution Strategy Training
RobustART: Benchmarking Robustness on Architecture Design and Training Techniques
The first comprehensive Robustness investigation benchmark on large-scale dataset ImageNet regarding ARchitecture design and Training techniques towards diverse noises.
Reimplement of SimSwap training code
SimSwap-train Reimplement of SimSwap training code Instructions 1.Environment Preparation (1)Refer to the README document of SIMSWAP to configure the
A repository that shares tuning results of trained models generated by TensorFlow / Keras. Post-training quantization (Weight Quantization, Integer Quantization, Full Integer Quantization, Float16 Quantization), Quantization-aware training. TensorFlow Lite. OpenVINO. CoreML. TensorFlow.js. TF-TRT. MediaPipe. ONNX. [.tflite,.h5,.pb,saved_model,tfjs,tftrt,mlmodel,.xml/.bin, .onnx]
PINTO_model_zoo Please read the contents of the LICENSE file located directly under each folder before using the model. My model conversion scripts ar
ConvNet training using pytorch
Convolutional networks using PyTorch This is a complete training example for Deep Convolutional Networks on various datasets (ImageNet, Cifar10, Cifar
PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
pytorch-fcn PyTorch implementation of Fully Convolutional Networks. Requirements pytorch = 0.2.0 torchvision = 0.1.8 fcn = 6.1.5 Pillow scipy tqdm
A self-hosted application that lets you create podcast RSS feeds from YouTube playlists
Playlist2Podcast A self-hosted application that lets you create podcast RSS feeds from YouTube playlists. What Does This Do? Takes a list of YouTube p
A self-supervised 3D representation learning framework named viewpoint bottleneck.
Pointly-supervised 3D Scene Parsing with Viewpoint Bottleneck Paper Created by Liyi Luo, Beiwen Tian, Hao Zhao and Guyue Zhou from Institute for AI In
PyTorch implementation of CVPR 2020 paper (Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence) and pre-trained model on ImageNet dataset
Reference-Based-Sketch-Image-Colorization-ImageNet This is a PyTorch implementation of CVPR 2020 paper (Reference-Based Sketch Image Colorization usin
Scripts for training an AI to play the endless runner Subway Surfers using a supervised machine learning approach by imitation and a convolutional neural network (CNN) for image classification
About subwAI subwAI - a project for training an AI to play the endless runner Subway Surfers using a supervised machine learning approach by imitation
Code for paper "Which Training Methods for GANs do actually Converge? (ICML 2018)"
GAN stability This repository contains the experiments in the supplementary material for the paper Which Training Methods for GANs do actually Converg
A Structured Self-attentive Sentence Embedding
Structured Self-attentive sentence embeddings Implementation for the paper A Structured Self-Attentive Sentence Embedding, which was published in ICLR
The PASS dataset: pretrained models and how to get the data - PASS: Pictures without humAns for Self-Supervised Pretraining
The PASS dataset: pretrained models and how to get the data - PASS: Pictures without humAns for Self-Supervised Pretraining
Apply Graph Self-Supervised Learning methods to graph-level task(TUDataset, MolculeNet Datset)
Graphlevel-SSL Overview Apply Graph Self-Supervised Learning methods to graph-level task(TUDataset, MolculeNet Dataset). It is unified framework to co
Tevatron is a simple and efficient toolkit for training and running dense retrievers with deep language models.
Tevatron Tevatron is a simple and efficient toolkit for training and running dense retrievers with deep language models. The toolkit has a modularized
PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
pytorch-fcn PyTorch implementation of Fully Convolutional Networks. Requirements pytorch = 0.2.0 torchvision = 0.1.8 fcn = 6.1.5 Pillow scipy tqdm
I decide to sync up this repo and self-critical.pytorch. (The old master is in old master branch for archive)
An Image Captioning codebase This is a codebase for image captioning research. It supports: Self critical training from Self-critical Sequence Trainin
TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP
TextAttack 🐙 Generating adversarial examples for NLP models [TextAttack Documentation on ReadTheDocs] About • Setup • Usage • Design About TextAttack
A2T: Towards Improving Adversarial Training of NLP Models (EMNLP 2021 Findings)
A2T: Towards Improving Adversarial Training of NLP Models This is the source code for the EMNLP 2021 (Findings) paper "Towards Improving Adversarial T
A machine learning library for spiking neural networks. Supports training with both torch and jax pipelines, and deployment to neuromorphic hardware.
Rockpool Rockpool is a Python package for developing signal processing applications with spiking neural networks. Rockpool allows you to build network
🐛 SSH self spreading worm written in python3 to propagate a botnet.
Mirkat SSH self spreading worm written in python3 to propagate a botnet. Install tutorial. cd ./script && sh setup.sh Support me. ⚠️ If this reposito
A self-supervised 3D representation learning framework named viewpoint bottleneck.
Pointly-supervised 3D Scene Parsing with Viewpoint Bottleneck Paper Created by Liyi Luo, Beiwen Tian, Hao Zhao and Guyue Zhou from Institute for AI In
Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR
Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR
Code of the paper "Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognition"
SEW (Squeezed and Efficient Wav2vec) The repo contains the code of the paper "Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speec
The training code for the 4th place model at MDX 2021 leaderboard A.
The training code for the 4th place model at MDX 2021 leaderboard A.
FireFlyer Record file format, writer and reader for DL training samples.
FFRecord The FFRecord format is a simple format for storing a sequence of binary records developed by HFAiLab, which supports random access and Linux
Code for the paper "Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds" (ICCV 2021)
Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds This is the official code implementation for the paper "Spatio-temporal Se
ROSITA: Enhancing Vision-and-Language Semantic Alignments via Cross- and Intra-modal Knowledge Integration
ROSITA News & Updates (24/08/2021) Release the demo to perform fine-grained semantic alignments using the pretrained ROSITA model. (15/08/2021) Releas
Object-aware Contrastive Learning for Debiased Scene Representation
Object-aware Contrastive Learning Official PyTorch implementation of "Object-aware Contrastive Learning for Debiased Scene Representation" by Sangwoo
CVPR 2021 - Official code repository for the paper: On Self-Contact and Human Pose.
TUCH This repo is part of our project: On Self-Contact and Human Pose. [Project Page] [Paper] [MPI Project Page] License Software Copyright License fo
It's a Discord bot to control your PC using your Discord Channel or using Reco: Discord PC Remote Controller App.
Reco PC Server Reco PC Server is a cross platform PC Controller Discord Bot which is a modified and improved version of Chimera for Reco-Discord PC Re
Your self hosted Youtube media server
The Tube Archivist Your self hosted Youtube media server Core functionality Subscribe to your favourite Youtube channels Download Videos using yt-dlp
Selene is a Python library and command line interface for training deep neural networks from biological sequence data such as genomes.
Selene is a Python library and command line interface for training deep neural networks from biological sequence data such as genomes.
This repository contains codes of ICCV2021 paper: SO-Pose: Exploiting Self-Occlusion for Direct 6D Pose Estimation
SO-Pose This repository contains codes of ICCV2021 paper: SO-Pose: Exploiting Self-Occlusion for Direct 6D Pose Estimation This paper is basically an
[EMNLP 2021] Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training
RoSTER The source code used for Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training, p
Official Pytorch implementation of Test-Agnostic Long-Tailed Recognition by Test-Time Aggregating Diverse Experts with Self-Supervision.
This repository is the official Pytorch implementation of Test-Agnostic Long-Tailed Recognition by Test-Time Aggregating Diverse Experts with Self-Supervision.
Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data
Real-ESRGAN Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data Ported from https://github.com/xinntao/Real-ESRGAN Depend
UniLM AI - Large-scale Self-supervised Pre-training across Tasks, Languages, and Modalities
Pre-trained (foundation) models across tasks (understanding, generation and translation), languages (100+ languages), and modalities (language, image, audio, vision + language, audio + language, etc.)
Galileo library for large scale graph training by JD
近年来,图计算在搜索、推荐和风控等场景中获得显著的效果,但也面临超大规模异构图训练,与现有的深度学习框架Tensorflow和PyTorch结合等难题。 Galileo(伽利略)是一个图深度学习框架,具备超大规模、易使用、易扩展、高性能、双后端等优点,旨在解决超大规模图算法在工业级场景的落地难题,提
Optimized code based on M2 for faster image captioning training
Transformer Captioning This repository contains the code for Transformer-based image captioning. Based on meshed-memory-transformer, we further optimi
The code for our paper "NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction"
The code for our paper "NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction"
A collection of self-contained and well-documented issues for newcomers to start contributing with
fedora-easyfix A collection of self-contained and well-documented issues for newcomers to start contributing with How to setup the local development e
Code and checkpoints for training the transformer-based Table QA models introduced in the paper TAPAS: Weakly Supervised Table Parsing via Pre-training.
End-to-end neural table-text understanding models.
Self-Supervised Pillar Motion Learning for Autonomous Driving (CVPR 2021)
Self-Supervised Pillar Motion Learning for Autonomous Driving Chenxu Luo, Xiaodong Yang, Alan Yuille Self-Supervised Pillar Motion Learning for Autono
Adaptive Pyramid Context Network for Semantic Segmentation (APCNet CVPR'2019)
Adaptive Pyramid Context Network for Semantic Segmentation (APCNet CVPR'2019) Introduction Official implementation of Adaptive Pyramid Context Network
Generate text line images for training deep learning OCR model (e.g. CRNN)
Generate text line images for training deep learning OCR model (e.g. CRNN)
Demonstration of the Model Training as a CI/CD System in Vertex AI
Model Training as a CI/CD System This project demonstrates the machine model training as a CI/CD system in GCP platform. You will see more detailed wo
Codes for CIKM'21 paper 'Self-Supervised Graph Co-Training for Session-based Recommendation'.
COTREC Codes for CIKM'21 paper 'Self-Supervised Graph Co-Training for Session-based Recommendation'. Requirements: Python 3.7, Pytorch 1.6.0 Best Hype
GeDML is an easy-to-use generalized deep metric learning library
GeDML is an easy-to-use generalized deep metric learning library
TAPEX: Table Pre-training via Learning a Neural SQL Executor
TAPEX: Table Pre-training via Learning a Neural SQL Executor The official repository which contains the code and pre-trained models for our paper TAPE
[ICCV21] Self-Calibrating Neural Radiance Fields
Self-Calibrating Neural Radiance Fields, ICCV, 2021 Project Page | Paper | Video Author Information Yoonwoo Jeong [Google Scholar] Seokjun Ahn [Google
[ICCV'2021] "SSH: A Self-Supervised Framework for Image Harmonization", Yifan Jiang, He Zhang, Jianming Zhang, Yilin Wang, Zhe Lin, Kalyan Sunkavalli, Simon Chen, Sohrab Amirghodsi, Sarah Kong, Zhangyang Wang
SSH: A Self-Supervised Framework for Image Harmonization (ICCV 2021) code for SSH Representative Examples Main Pipeline RealHM DataSet Google Drive Pr
This solves the autonomous driving issue which is supported by deep learning technology. Given a video, it splits into images and predicts the angle of turning for each frame.
Self Driving Car An autonomous car (also known as a driverless car, self-driving car, and robotic car) is a vehicle that is capable of sensing its env
Unofficial implementation of Perceiver IO: A General Architecture for Structured Inputs & Outputs
Perceiver IO Unofficial implementation of Perceiver IO: A General Architecture for Structured Inputs & Outputs Usage import torch from src.perceiver.
Ongoing research training transformer language models at scale, including: BERT & GPT-2
Megatron (1 and 2) is a large, powerful transformer developed by the Applied Deep Learning Research team at NVIDIA.
Implementation for paper: Self-Regulation for Semantic Segmentation
Self-Regulation for Semantic Segmentation This is the PyTorch implementation for paper Self-Regulation for Semantic Segmentation, ICCV 2021. Citing SR
[ICCV 2021] Official Pytorch implementation for Discriminative Region-based Multi-Label Zero-Shot Learning SOTA results on NUS-WIDE and OpenImages
Discriminative Region-based Multi-Label Zero-Shot Learning (ICCV 2021) [arXiv][Project page coming soon] Sanath Narayan*, Akshita Gupta*, Salman Kh
🐛 Self spreading Botnet based on Mirai C&C Arch, spreading through SSH and Telnet protocol.
HBot Self spreading Botnet based on Mirai C&C Arch, spreading through SSH and Telnet protocol. Modern script fullly written in python3. Warning. This
[ICCV 2021] Official Pytorch implementation for Discriminative Region-based Multi-Label Zero-Shot Learning SOTA results on NUS-WIDE and OpenImages
Discriminative Region-based Multi-Label Zero-Shot Learning (ICCV 2021) [arXiv][Project page coming soon] Sanath Narayan*, Akshita Gupta*, Salman Kh
A pytorch implementation of Paper "Improved Training of Wasserstein GANs"
WGAN-GP An pytorch implementation of Paper "Improved Training of Wasserstein GANs". Prerequisites Python, NumPy, SciPy, Matplotlib A recent NVIDIA GPU
Code used to generate the results appearing in "Train longer, generalize better: closing the generalization gap in large batch training of neural networks"
Train longer, generalize better - Big batch training This is a code repository used to generate the results appearing in "Train longer, generalize bet
Accelerate Neural Net Training by Progressively Freezing Layers
FreezeOut A simple technique to accelerate neural net training by progressively freezing layers. This repository contains code for the extended abstra
Pytorch implementation of "Forward Thinking: Building and Training Neural Networks One Layer at a Time"
forward-thinking-pytorch Pytorch implementation of Forward Thinking: Building and Training Neural Networks One Layer at a Time Requirements Python 2.7
This is the offical website for paper ''Category-consistent deep network learning for accurate vehicle logo recognition''
The Pytorch Implementation of Category-consistent deep network learning for accurate vehicle logo recognition This is the offical website for paper ''
Unofficial Alias-Free GAN implementation. Based on rosinality's version with expanded training and inference options.
Alias-Free GAN An unofficial version of Alias-Free Generative Adversarial Networks (https://arxiv.org/abs/2106.12423). This repository was heavily bas
[Preprint] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study Codes for [Preprint] Bag of Tricks for Training Deeper Graph
PyTorch implementation of our ICCV2021 paper: StructDepth: Leveraging the structural regularities for self-supervised indoor depth estimation
StructDepth PyTorch implementation of our ICCV2021 paper: StructDepth: Leveraging the structural regularities for self-supervised indoor depth estimat
Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training
Flood Detection Challenge This repository contains code for our submission to the ETCI 2021 Competition on Flood Detection (Winning Solution #2). Acco
ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation
ST++ This is the official PyTorch implementation of our paper: ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation. Lihe Ya
[TIP 2021] SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction
SADRNet Paper link: SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction Requirements python
Official code for "Focal Self-attention for Local-Global Interactions in Vision Transformers"
Focal Transformer This is the official implementation of our Focal Transformer -- "Focal Self-attention for Local-Global Interactions in Vision Transf
A PyTorch implementation of "Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning", IJCAI-21
MERIT A PyTorch implementation of our IJCAI-21 paper Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning. Depen
We present a framework for training multi-modal deep learning models on unlabelled video data by forcing the network to learn invariances to transformations applied to both the audio and video streams.
Multi-Modal Self-Supervision using GDT and StiCa This is an official pytorch implementation of papers: Multi-modal Self-Supervision from Generalized D
PyTorch DepthNet Training on Still Box dataset
DepthNet training on Still Box Project page This code can replicate the results of our paper that was published in UAVg-17. If you use this repo in yo
An attendance bot that joins google meet automatically according to schedule and marks present in the google meet.
Google-meet-self-attendance-bot An attendance bot which joins google meet automatically according to schedule and marks present in the google meet. I
PyTorch implementation of MoCo v3 for self-supervised ResNet and ViT.
MoCo v3 for Self-supervised ResNet and ViT Introduction This is a PyTorch implementation of MoCo v3 for self-supervised ResNet and ViT. The original M
Official implementation of the ICCV 2021 paper "Conditional DETR for Fast Training Convergence".
The DETR approach applies the transformer encoder and decoder architecture to object detection and achieves promising performance. In this paper, we handle the critical issue, slow training convergence, and present a conditional cross-attention mechanism for fast DETR training. Our approach is motivated by that the cross-attention in DETR relies highly on the content embeddings and that the spatial embeddings make minor contributions, increasing the need for high-quality content embeddings and thus increasing the training difficulty.
Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation (ICCV2021)
Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation This is a pytorch project for the paper Dynamic Divide-and-Conquer Ad