Python Self-critical-sequence-training Resources

Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training [Arxiv] VideoMAE: Masked Autoencoders are Data-Efficient Learne

Dataset Distillation by Matching Training Trajectories Project Page | Paper This repo contains code for training expert trajectories and distilling sy

SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image [Paper] [Website] Pipeline Code Environment pip install -r requirements

PoseTriplet: Co-evolving 3D Human Pose Estimation, Imitation, and Hallucination under Self-supervision Kehong Gong*, Bingbing Li*, Jianfeng Zhang*, Ta

🎓 Data Analysis and Model Training Course by Global AI Hub Syllabus: Day 1 What is Data? Multimedia Structured and Unstructured Data Data Types Data

Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks (ICCV 2021) This repository is the official implem

Explorer Explorer is a Autonomous (self-hosted) Bittorrent Network Search Engine. About The Project Screenshots Supported features Number Feature 1 DH

Versatile Multi-Modal Pre-Training for Human-Centric Perception Fangzhou Hong1  Liang Pan1  Zhongang Cai1,2,3  Ziwei Liu1* 1S-Lab, Nanyang Technologic

cloob-training Pretrained models There are two pretrained CLOOB models in this repo at the moment, a 16 epoch and a 32 epoch ViT-B/16 checkpoint train

SageMaker Studio Lab Sample Notebooks Available today in public preview. If you are looking for a no-cost compute environment to run Jupyter notebooks

MetaShift: A Dataset of Datasets for Evaluating Distribution Shifts and Training Conflicts This repo provides the PyTorch source code of our paper: Me

BigDetection: A Large-scale Benchmark for Improved Object Detector Pre-training By Likun Cai, Zhi Zhang, Yi Zhu, Li Zhang, Mu Li, Xiangyang Xue. This

Mugs: A Multi-Granular Self-Supervised Learning Framework This is a PyTorch implementation of Mugs proposed by our paper "Mugs: A Multi-Granular Self-

Coreferee Author: Richard Paul Hudson, Explosion AI 1. Introduction 1.1 The basic idea 1.2 Getting started 1.2.1 English 1.2.2 French 1.2.3 German 1.2

Self-Supervised Models are Continual Learners This is the official repository for the paper: Self-Supervised Models are Continual Learners Enrico Fini

FreeSOLO: Learning to Segment Objects without Annotations This project hosts the code for implementing the FreeSOLO algorithm for unsupervised instanc

pytorch-lifestream a library built upon PyTorch for building embeddings on discrete event sequences using self-supervision. It can process terabyte-si

LAV Learning from All Vehicles Dian Chen, Philipp Krähenbühl CVPR 2022 (also arXiV 2203.11934) This repo contains code for paper Learning from all veh

Crafting Better Contrastive Views for Siamese Representation Learning (CVPR 2022 Oral) 2022-03-29: The paper was selected as a CVPR 2022 Oral paper! 2

hpc-training-2022 Repository for training material for the 2022 SDSC HPC/CI Training Series HPC/CI Training Series home https://www.sdsc.edu/event_ite

English | 简体中文 Easy Parallel Library Overview Easy Parallel Library (EPL) is a general and efficient library for distributed model training. Usability

Vision-Language Pre-Training with Triple Contrastive Learning, CVPR 2022 News (03/16/2022) upload retrieval checkpoints finetuned on COCO and Flickr T

CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding (CVPR'22) Paper Link | Project Page Abstract : Manual an

💎A high level pipeline for face landmarks detection, supports training, evaluating, exporting, inference and 100+ data augmentations, compatible with torchvision and albumentations, can easily install with pip.

Unsupervised Phone and Word Segmentation using Vector-Quantized Neural Networks Overview Unsupervised phone and word segmentation on speech data is pe

CaiT-TF (Going deeper with Image Transformers) This repository provides TensorFlow / Keras implementations of different CaiT [1] variants from Touvron

LG-AI-Challenge-for-Plant-Classification Dacon에서 진행된 농업 환경 변화에 따른 작물 병해 진단 AI 경진대회 에 대한 코드입니다. (colab directory에 코드가 잘 정리 되어있습니다.) Requirements python

Azpn-Azure-Free-VPN Azure free vpn for students only! (Self hosted/No sketchy services/Fast and free) This is an alternative secure way of accessing f

rich-msa A simple module to render colorful Multiple Sequence Alignment with rich in the terminal. 🔧 Installing Install the rich-msa package directly

As-ViT: Auto-scaling Vision Transformers without Training [PDF] Wuyang Chen, Wei Huang, Xianzhi Du, Xiaodan Song, Zhangyang Wang, Denny Zhou In ICLR 2

data2vec-pytorch PyTorch implementation of "data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language" from Meta AI (F

(CVPR 2022) TokenCut Pytorch implementation of Tokencut: Self-supervised Transformers for Unsupervised Object Discovery using Normalized Cut Yangtao W

Italian CLIP CLIP (Radford et al., 2021) is a multimodal model that can learn to represent images and text jointly in the same space. In this project,

Hugging Face Optimum 🤗 Optimum is an extension of 🤗 Transformers, providing a set of performance optimization tools enabling maximum efficiency to t

Paper | Blog OFA is a unified multimodal pretrained model that unifies modalities (i.e., cross-modality, vision, language) and tasks (e.g., image gene

Behavior-Sequence-Transformer-Pytorch This is a pytorch implementation for the BST model from Alibaba https://arxiv.org/pdf/1905.06874.pdf This model

DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks Abstract: Adversarial training has been proven to

Potato Disease Classification Setup for Python: Install Python (Setup instructions) Install Python packages pip3 install -r training/requirements.txt

Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology Self-Supervised Vision Transformers Learn Visual Concepts in Histopatholog

TorchMultimodal (Alpha Release) Introduction TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.

A Self-Supervised Descriptor for Image Copy Detection (SSCD) This is the open-source codebase for "A Self-Supervised Descriptor for Image Copy Detecti

PromptDet: Expand Your Detector Vocabulary with Uncurated Images Paper Website Introduction The goal of this work is to establish a scalable pipeline

SelfRemaster: Self-Supervised Speech Restoration Official implementation of SelfRemaster: Self-Supervised Speech Restoration with Analysis-by-Synthesi

AMRBART An implementation for ACL2022 paper "Graph Pre-training for AMR Parsing and Generation". You may find our paper here (Arxiv). Requirements pyt

LightHuBERT LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERT | Github | Huggingface | SUPER

🔍 Watermarking Images in Self-Supervised Latent-Spaces PyTorch implementation and pretrained models for the paper. For details, see Watermarking Imag

AMOS This repository contains the scripts for fine-tuning AMOS pretrained models on GLUE and SQuAD 2.0 benchmarks. Paper: Pretraining Text Encoders wi

beyond masking Beyond Masking: Demystifying Token-Based Pre-Training for Vision Transformers The code is coming Figure 1: Pipeline of token-based pre-

LUPerson-NL Large-Scale Pre-training for Person Re-identification with Noisy Labels (LUPerson-NL) The repository is for our CVPR2022 paper Large-Scale

Introduction This codebase contains source-code of the Python-based implementation (ARES) of our SIGIR 2022 paper. Chen, Jia, et al. "Axiomatically Re

CLIP-GEN [简体中文][English] 本项目在萤火二号集群上用 PyTorch 实现了论文 《CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP》。 CLIP-GEN 是一个 Language-F

DeepGNN Overview DeepGNN is a framework for training machine learning models on large scale graph data. DeepGNN contains all the necessary features in

SD-AANet The code is for the paper "A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentation" [arxiv] Overview confi

Aiming at the common training datsets split, spectrum preprocessing, wavelength select and calibration models algorithm involved in the spectral analysis process, a complete algorithm library is established, which is named opensa (openspectrum analysis).

This repository provides a library for efficient training of masked language models (MLM), built with fairseq. We fork fairseq to give researchers mor

CharacterBERT-DR The offcial repository for CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typos, Sh

OD-Rec Codes for SIGIR'22 Paper 'On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation' Paper, saved teacher models and Andro

Description: ProtFeat is designed to extract the protein features by employing POSSUM and iFeature python-based tools. ProtFeat includes a total of 39

P3 Ranker Implementation for our SIGIR2022 accepted paper: P3 Ranker: Mitigating the Gaps between Pre-training and Ranking Fine-tuning with Prompt-bas

RODD Official Implementation of 2022 CVPRW Paper RODD: A Self-Supervised Approach for Robust Out-of-Distribution Detection Introduction: Recent studie

ITTR - Pytorch Implementation of the Hybrid Perception Block (HPB) and Dual-Pruned Self-Attention (DPSA) block from the ITTR paper for Image to Image

Kaggle Competition: Forest Cover Type Prediction In this project we predict the forest cover type (the predominant kind of tree cover) using the carto

Bridging the Data Gap between Training and Inference for Unsupervised Neural Machine Translation This is the implementaion of our paper: Bridging the

DNN Training, from theory to practice This repository is complementary to the deep learning training lesson given to les Mines ParisTech on the 11th o

STEMM: Self-learning with Speech-Text Manifold Mixup for Speech Translation This is a PyTorch implementation for the ACL 2022 main conference paper ST

Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots Blind2Unblind Citing Blind2Unblind @inproceedings{wang2022blind2unblind, tit

The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy Codes for this paper: [CVPR 2022] The Pr

KeunoBot 🐼 -Simple Self-Bot for Discord KEUNOBOT 🐼 - Run KeunoBot : /* - Install KeunoBot - Extract it - Run setup.bat - Set token and prefi

Memory Efficient Attention Pytorch Implementation of a memory efficient multi-head attention as proposed in the paper, Self-attention Does Not Need O(

Self-driving car with RL stable baseline3 Most of the project develop from https://github.com/GerardMaggiolino/Gym-Medium-Post Please check it out! Th

architecture-traning Architecture Patterns with Python (TDD, DDD, EDM) Chapter 5. 높은 기어비와 낮은 기어비의 TDD 5.2 도메인 계층 테스트를 서비스 계층으로 옮겨야 하는가? 도메인 계층 테스트 def

Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation Simple implementation of our paper MVGC. The d

End-to-end Music Remastering System This repository includes source code and pre

Super-Fast-Adversarial-Training This is a PyTorch Implementation code for develo

smart_edu-autobooking Sistema di autoprenotazione per l'aula studio Johnson@DMI-

discord-selfbot Very basic discord self bot still being actively developed requi

HashNeRF-pytorch Instant-NGP recently introduced a Multi-resolution Hash Encodin

Fibonaaci Series Generating the Fibonacci sequence is a classic recursive proble

Code and Datasets from the paper "Self-supervised contrastive learning for volcanic unrest detection from InSAR data" You can download the pretrained

Official repository of OFA. Paper: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework

[ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training The Unreasonable Effectiveness of

LyaNet: A Lyapunov Framework for Training Neural ODEs Provide the model type--config-name to train and test models configured as those shown in the pa

This is the replication package for paper submission: Towards Training Reproducible Deep Learning Models.

Minimal implementation of Decision Transformer: Reinforcement Learning via Sequence Modeling in PyTorch for mujoco control tasks in OpenAI gym

A Broad Study on the Transferability of Visual Representations with Contrastive Learning This repository contains code for the paper: A Broad Study on

Code for CCA-SSG model proposed in the NeurIPS 2021 paper From Canonical Correlation Analysis to Self-supervised Graph Neural Networks.

Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks This repository contains the code and data for the corresp

Cement-Strength-Prediction Problem Statement To build a regression model to predict the concrete compressive strength based on the different features

py-self-organizing-maps Simple implementation of self-organizing maps (SOMs) A SOM is an unsupervised method for learning a mapping from a discrete ne

Parallel web scraping The project is a training task for web scraping using python multithreading and a real-time-updated list of available proxy serv

Official code of Retinal Vessel Segmentation with Pixel-wise Adaptive Filters and Consistency Training (ISBI 2022)

SuperGen The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding. Requirements Before running, you

SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification

Byzantine-robust decentralized learning via self-centered clipping In this paper, we study the challenging task of Byzantine-robust decentralized trai

A mini-scale reproduction code of the AlphaStar program. Note: the original AlphaStar is the AI proposed by DeepMind to play StarCraft II.

FewBit FewBit — a library for memory efficient training of large neural networks. Its efficiency originates from storage optimizations applied to back

DNA sequence classification by Deep Neural Network: Project Overview worked on the DNA sequence classification problem where the input is the DNA sequ

py-self-organizing-map Simple implementation of Self Organizing Maps (SOMs) with rectangular and hexagonal grid topologies. A SOM is a simple unsuperv

Regression Transformer Codebase to experiment with a hybrid Transformer that combines conditional sequence generation with regression . Development se

Differentially private Imagenet training Code for the tech report Toward Training at ImageNet Scale with Differential Privacy by Alexey Kurakin, Steve