5993 Repositories
Python multi-domain-learning Libraries
SentAugment is a data augmentation technique for semi-supervised learning in NLP.
SentAugment SentAugment is a data augmentation technique for semi-supervised learning in NLP. It uses state-of-the-art sentence embeddings to structur
A single model that parses Universal Dependencies across 75 languages.
A single model that parses Universal Dependencies across 75 languages. Given a sentence, jointly predicts part-of-speech tags, morphology tags, lemmas, and dependency trees.
PyTorch code for EMNLP 2019 paper "LXMERT: Learning Cross-Modality Encoder Representations from Transformers".
LXMERT: Learning Cross-Modality Encoder Representations from Transformers Our servers break again :(. I have updated the links so that they should wor
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:
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
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
[CVPR 2021] VirTex: Learning Visual Representations from Textual Annotations
VirTex: Learning Visual Representations from Textual Annotations Karan Desai and Justin Johnson University of Michigan CVPR 2021 arxiv.org/abs/2006.06
Dense Passage Retriever - is a set of tools and models for open domain Q&A task.
Dense Passage Retrieval Dense Passage Retrieval (DPR) - is a set of tools and models for state-of-the-art open-domain Q&A research. It is based on the
Train Dense Passage Retriever (DPR) with a single GPU
Gradient Cached Dense Passage Retrieval Gradient Cached Dense Passage Retrieval (GC-DPR) - is an extension of the original DPR library. We introduce G
Toolkit for developing and maintaining ML models
modelkit Python framework for production ML systems. modelkit is a minimalist yet powerful MLOps library for Python, built for people who want to depl
Learn Python Regular Expressions step by step from beginner to advanced levels
Python re(gex)? Learn Python Regular Expressions step by step from beginner to advanced levels with hundreds of examples and exercises The book also i
Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle
DOC | Quick Start | 中文 Breaking News !! 🔥 🔥 🔥 OGB-LSC KDD CUP 2021 winners announced!! (2021.06.17) Super excited to announce our PGL team won TWO
The official implementation of Relative Uncertainty Learning for Facial Expression Recognition
Relative Uncertainty Learning for Facial Expression Recognition The official implementation of the following paper at NeurIPS2021: Title: Relative Unc
[NeurIPS'21 Spotlight] PyTorch code for our paper "Aligned Structured Sparsity Learning for Efficient Image Super-Resolution"
ASSL This repository is for a new network pruning method (Aligned Structured Sparsity Learning, ASSL) for efficient single image super-resolution (SR)
[NeurIPS-2021] Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation
Efficient Graph Similarity Computation - (EGSC) This repo contains the source code and dataset for our paper: Slow Learning and Fast Inference: Effici
Code and Data for the paper: Molecular Contrastive Learning with Chemical Element Knowledge Graph [AAAI 2022]
Knowledge-enhanced Contrastive Learning (KCL) Molecular Contrastive Learning with Chemical Element Knowledge Graph [ AAAI 2022 ]. We construct a Chemi
Learn to code in any language. If
Learn to Code It is an intiiative undertaken by Student Ambassadors Club, Jamshoro for students who are absolute begineers in programming and want to
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
Deep Q Learning with OpenAI Gym and Pokemon Showdown
pokemon-deep-learning An openAI gym project for pokemon involving deep q learning. Made by myself, Sam Little, and Layton Webber. This code captures g
PLUR is a collection of source code datasets suitable for graph-based machine learning.
PLUR (Programming-Language Understanding and Repair) is a collection of source code datasets suitable for graph-based machine learning. We provide scripts for downloading, processing, and loading the datasets. This is done by offering a unified API and data structures for all datasets.
Code for A Volumetric Transformer for Accurate 3D Tumor Segmentation
VT-UNet This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmentaion results of VT-UNet. Environmen
Implementation of "Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency"
Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency (ICCV2021) Paper Link: https://arxiv.org/abs/2107.11355 This implementation bui
Implementation of "Semi-supervised Domain Adaptive Structure Learning"
Semi-supervised Domain Adaptive Structure Learning - ASDA This repo contains the source code and dataset for our ASDA paper. Illustration of the propo
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
Upgini : data search library for your machine learning pipelines
Automated data search library for your machine learning pipelines → find & deliver relevant external data & features to boost ML accuracy :chart_with_upwards_trend:
Learning to Rewrite for Non-Autoregressive Neural Machine Translation
RewriteNAT This repo provides the code for reproducing our proposed RewriteNAT in EMNLP 2021 paper entitled "Learning to Rewrite for Non-Autoregressiv
Fuck - Multi Brute Force 🚶♂
f-mbf Fuck - Multi Brute Force 🚶♂ Install Script $ pkg update && pkg upgrade $ pkg install python2 $ pkg install git $ pip2 install requests $ pip2
Behind the Curtain: Learning Occluded Shapes for 3D Object Detection
Behind the Curtain: Learning Occluded Shapes for 3D Object Detection Acknowledgement We implement our model, BtcDet, based on [OpenPcdet 0.3.0]. Insta
Built on python (Mathematical straight fit line coordinates error predictor machine learning foundational model)
Sum-Square_Error-Business-Analytical-Tool- Built on python (Mathematical straight fit line coordinates error predictor machine learning foundational m
Multi-Process / Censorship Detection
Multi-Process / Censorship Detection
A module to prevent invites and joins to Matrix rooms by checking the involved server(s)' domain.
Synapse Domain Rule Checker A module to prevent invites and joins to Matrix rooms by checking the involved server(s)' domain. Installation From the vi
Milano is a tool for automating hyper-parameters search for your models on a backend of your choice.
Milano (This is a research project, not an official NVIDIA product.) Documentation https://nvidia.github.io/Milano Milano (Machine learning autotuner
Code release for Hu et al., Learning to Segment Every Thing. in CVPR, 2018.
Learning to Segment Every Thing This repository contains the code for the following paper: R. Hu, P. Dollár, K. He, T. Darrell, R. Girshick, Learning
Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.
Core ML Tools Use coremltools to convert machine learning models from third-party libraries to the Core ML format. The Python package contains the sup
Convenient script for trading with python.
Convenient script for trading with python.
Open source annotation tool for machine learning practitioners.
doccano doccano is an open source text annotation tool for humans. It provides annotation features for text classification, sequence labeling and sequ
MAME is a multi-purpose emulation framework.
MAME's purpose is to preserve decades of software history. As electronic technology continues to rush forward, MAME prevents this important "vintage" software from being lost and forgotten.
Multi-user server for Jupyter notebooks
Technical Overview | Installation | Configuration | Docker | Contributing | License | Help and Resources Please note that this repository is participa
DISTIL: Deep dIverSified inTeractIve Learning.
DISTIL: Deep dIverSified inTeractIve Learning. An active/inter-active learning library built on py-torch for reducing labeling costs.
OOD Generalization and Detection (ACL 2020)
Pretrained Transformers Improve Out-of-Distribution Robustness How does pretraining affect out-of-distribution robustness? We create an OOD benchmark
EMNLP 2021 paper The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers.
Codebase for training transformers on systematic generalization datasets. The official repository for our EMNLP 2021 paper The Devil is in the Detail:
Code for the paper "Are Sixteen Heads Really Better than One?"
Are Sixteen Heads Really Better than One? This repository contains code to reproduce the experiments in our paper Are Sixteen Heads Really Better than
The repository for the paper "When Do You Need Billions of Words of Pretraining Data?"
pretraining-learning-curves This is the repository for the paper When Do You Need Billions of Words of Pretraining Data? Edge Probing We use jiant1 fo
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
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
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
This is the code for Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning
This is the code for Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning It includes /bert, which is the original BERT repos
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization (ACL 2021)
Structured Super Lottery Tickets in BERT This repo contains our codes for the paper "Super Tickets in Pre-Trained Language Models: From Model Compress
Research code for "What to Pre-Train on? Efficient Intermediate Task Selection", EMNLP 2021
efficient-task-transfer This repository contains code for the experiments in our paper "What to Pre-Train on? Efficient Intermediate Task Selection".
Multi-Task Deep Neural Networks for Natural Language Understanding
New Release We released Adversarial training for both LM pre-training/finetuning and f-divergence. Large-scale Adversarial training for LMs: ALUM code
Codes for our paper The Stem Cell Hypothesis: Dilemma behind Multi-Task Learning with Transformer Encoders published to EMNLP 2021.
The Stem Cell Hypothesis Codes for our paper The Stem Cell Hypothesis: Dilemma behind Multi-Task Learning with Transformer Encoders published to EMNLP
PyTorch implementation of the ACL, 2021 paper Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks.
Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks This repo contains the PyTorch implementation of the ACL, 2021 pa
Pytorch implementation of Bert and Pals: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning
PyTorch implementation of BERT and PALs Introduction Work by Asa Cooper Stickland and Iain Murray, University of Edinburgh. Code for BERT and PALs; mo
Adapter-BERT: Parameter-Efficient Transfer Learning for NLP.
Adapter-BERT: Parameter-Efficient Transfer Learning for NLP.
Zero-shot Learning by Generating Task-specific Adapters
Code for "Zero-shot Learning by Generating Task-specific Adapters" This is the repository containing code for "Zero-shot Learning by Generating Task-s
This repository contains the code for "Exploiting Cloze Questions for Few-Shot Text Classification and Natural Language Inference"
Pattern-Exploiting Training (PET) This repository contains the code for Exploiting Cloze Questions for Few-Shot Text Classification and Natural Langua
ACL'2021: LM-BFF: Better Few-shot Fine-tuning of Language Models
LM-BFF (Better Few-shot Fine-tuning of Language Models) This is the implementation of the paper Making Pre-trained Language Models Better Few-shot Lea
EasyTransfer is designed to make the development of transfer learning in NLP applications easier.
EasyTransfer is designed to make the development of transfer learning in NLP applications easier. The literature has witnessed the success of applying
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
PyTorch source code of NAACL 2019 paper "An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language Models"
This repository contains source code for NAACL 2019 paper "An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language Models" (P
EMNLP 2021 paper "Pre-train or Annotate? Domain Adaptation with a Constrained Budget".
Pre-train or Annotate? Domain Adaptation with a Constrained Budget This repo contains code and data associated with EMNLP 2021 paper "Pre-train or Ann
Source code for the ACL-IJCNLP 2021 paper entitled "T-DNA: Taming Pre-trained Language Models with N-gram Representations for Low-Resource Domain Adaptation" by Shizhe Diao et al.
T-DNA Source code for the ACL-IJCNLP 2021 paper entitled Taming Pre-trained Language Models with N-gram Representations for Low-Resource Domain Adapta
Information Gain Filtration (IGF) is a method for filtering domain-specific data during language model finetuning. IGF shows significant improvements over baseline fine-tuning without data filtration.
Information Gain Filtration Information Gain Filtration (IGF) is a method for filtering domain-specific data during language model finetuning. IGF sho
🥇Samsung AI Challenge 2021 1등 솔루션입니다🥇
MoT - Molecular Transformer Large-scale Pretraining for Molecular Property Prediction Samsung AI Challenge for Scientific Discovery This repository is
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]
DANeS is an open-source E-newspaper dataset by collaboration between DATASET JSC (dataset.vn) and AIV Group (aivgroup.vn)
DANeS - Open-source E-newspaper dataset Source: Technology vector created by macrovector - www.freepik.com. DANeS is an open-source E-newspaper datase
ExCon: Explanation-driven Supervised Contrastive Learning
ExCon: Explanation-driven Supervised Contrastive Learning Link to the paper: https://arxiv.org/pdf/2111.14271.pdf Contributors of this repo: Zhibo Zha
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.
Official implementation for the paper "Attentive Prototypes for Source-free Unsupervised Domain Adaptive 3D Object Detection"
Attentive Prototypes for Source-free Unsupervised Domain Adaptive 3D Object Detection PyTorch code release of the paper "Attentive Prototypes for Sour
TensorFlow (Python) implementation of DeepTCN model for multivariate time series forecasting.
DeepTCN TensorFlow TensorFlow (Python) implementation of multivariate time series forecasting model introduced in Chen, Y., Kang, Y., Chen, Y., & Wang
Code for DeepCurrents: Learning Implicit Representations of Shapes with Boundaries
DeepCurrents | Webpage | Paper DeepCurrents: Learning Implicit Representations of Shapes with Boundaries David Palmer*, Dmitriy Smirnov*, Stephanie Wa
Code release for "Conditional Adversarial Domain Adaptation" (NIPS 2018)
CDAN Code release for "Conditional Adversarial Domain Adaptation" (NIPS 2018) New version: https://github.com/thuml/Transfer-Learning-Library Dataset
code for our ECCV 2020 paper "A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation"
Code for our ECCV (2020) paper A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation. Prerequisites: python == 3.6.8 pytorch ==1.1.0
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
Label Studio is a multi-type data labeling and annotation tool with standardized output format
Website • Docs • Twitter • Join Slack Community What is Label Studio? Label Studio is an open source data labeling tool. It lets you label data types
A deep learning based semantic search platform that computes similarity scores between provided query and documents
semanticsearch This is a deep learning based semantic search platform that computes similarity scores between provided query and documents. Documents
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
A general framework for deep learning experiments under PyTorch based on pytorch-lightning
torchx Torchx is a general framework for deep learning experiments under PyTorch based on pytorch-lightning. TODO list gan-like training wrapper text
Implementation of Vaswani, Ashish, et al. "Attention is all you need."
Attention Is All You Need Paper Implementation This is my from-scratch implementation of the original transformer architecture from the following pape
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
Multi-path load balancing is a method used by most of the real-time network to split the packets into different paths rather than transferring it through a single path
Multipath-Load-Balancing Method of managing incoming traffic by distributing and sharing load fairly among multiple routes from source to destination
AML Command Transfer. A lightweight tool to transfer any command line to Azure Machine Learning Services
AML Command Transfer (ACT) ACT is a lightweight tool to transfer any command from the local machine to AML or ITP, both of which are Azure Machine Lea
A simple image-level annotation tool supporting multi-channel images for napari.
napari-labelimg4classification A simple image-level annotation tool supporting multi-channel images for napari. This napari plugin was generated with
Using deep learning to predict gene structures of the coding genes in DNA sequences of Arabidopsis thaliana
DeepGeneAnnotator: A tool to annotate the gene in the genome The master thesis of the "Using deep learning to predict gene structures of the coding ge
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
Open source person re-identification library in python
Open-ReID Open-ReID is a lightweight library of person re-identification for research purpose. It aims to provide a uniform interface for different da
UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss
UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss This repository contains the TensorFlow implementation of the paper UnF
ClearML - Auto-Magical Suite of tools to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
ClearML - Auto-Magical Suite of tools to streamline your ML workflow Experiment Manager, MLOps and Data-Management ClearML Formerly known as Allegro T
Evaluating Privacy-Preserving Machine Learning in Critical Infrastructures: A Case Study on Time-Series Classification
PPML-TSA This repository provides all code necessary to reproduce the results reported in our paper Evaluating Privacy-Preserving Machine Learning in
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
DeepAL: Deep Active Learning in Python
DeepAL: Deep Active Learning in Python Python implementations of the following active learning algorithms: Random Sampling Least Confidence [1] Margin
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-Learning
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-Learning This is the official repository of "Camera Distortion-
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
Official implementation for the paper "Attentive Prototypes for Source-free Unsupervised Domain Adaptive 3D Object Detection"
Attentive Prototypes for Source-free Unsupervised Domain Adaptive 3D Object Detection PyTorch code release of the paper "Attentive Prototypes for Sour
PyContinual (An Easy and Extendible Framework for Continual Learning)
PyContinual (An Easy and Extendible Framework for Continual Learning) Easy to Use You can sumply change the baseline, backbone and task, and then read
Multi-Template Mouse Brain MRI Atlas (MBMA): both in-vivo and ex-vivo
Multi-template MRI mouse brain atlas (both in vivo and ex vivo) Mouse Brain MRI atlas (both in-vivo and ex-vivo) (repository relocated from the origin
Code for Estimating Multi-cause Treatment Effects via Single-cause Perturbation (NeurIPS 2021)
Estimating Multi-cause Treatment Effects via Single-cause Perturbation (NeurIPS 2021) Single-cause Perturbation (SCP) is a framework to estimate the m
Code for the paper "Functional Regularization for Reinforcement Learning via Learned Fourier Features"
Reinforcement Learning with Learned Fourier Features State-space Soft Actor-Critic Experiments Move to the state-SAC-LFF repository. cd state-SAC-LFF