620 Repositories
Python unsupervised-domain-adaptation Libraries
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
These are the materials for the paper "Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations"
Few-shot-NLEs These are the materials for the paper "Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations". You can find the smal
Supervised & unsupervised machine-learning techniques are applied to the database of weighted P4s which admit Calabi-Yau hypersurfaces.
Weighted Projective Spaces ML Description: The database of 5-vectors describing 4d weighted projective spaces which admit Calabi-Yau hypersurfaces are
ANEA: Automated (Named) Entity Annotation for German Domain-Specific Texts
ANEA The goal of Automatic (Named) Entity Annotation is to create a small annotated dataset for NER extracted from German domain-specific texts. Insta
Adaptation through prediction: multisensory active inference torque control
Adaptation through prediction: multisensory active inference torque control Submitted to IEEE Transactions on Cognitive and Developmental Systems Abst
Internationalized Domain Names for Python (IDNA 2008 and UTS #46)
Internationalized Domain Names in Applications (IDNA) Support for the Internationalised Domain Names in Applications (IDNA) protocol as specified in R
InDuDoNet+: A Model-Driven Interpretable Dual Domain Network for Metal Artifact Reduction in CT Images
InDuDoNet+: A Model-Driven Interpretable Dual Domain Network for Metal Artifact Reduction in CT Images Hong Wang, Yuexiang Li, Haimiao Zhang, Deyu Men
Official implementation of the article "Unsupervised JPEG Domain Adaptation For Practical Digital Forensics"
Unsupervised JPEG Domain Adaptation for Practical Digital Image Forensics @WIFS2021 (Montpellier, France) Rony Abecidan, Vincent Itier, Jeremie Boulan
Simple application that does transformation with HPF and LPFs.
Simple application that applies Butterworth, Gaussian & Ideal kernels on HPF and LPFs -aka Frequency Domain Filtering- Upload image from sidebar, set
Exploiting CVE-2021-42278 and CVE-2021-42287 to impersonate DA from standard domain user
Exploiting CVE-2021-42278 and CVE-2021-42287 to impersonate DA from standard domain user Known issues it will not work outside kali , i will update it
CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation
CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation [arxiv] This is the official repository for CDTrans: Cross-domain Transformer for
Cycle Consistent Adversarial Domain Adaptation (CyCADA)
Cycle Consistent Adversarial Domain Adaptation (CyCADA) A pytorch implementation of CyCADA. If you use this code in your research please consider citi
Code accompanying "Adaptive Methods for Aggregated Domain Generalization"
Adaptive Methods for Aggregated Domain Generalization (AdaClust) Official Pytorch Implementation of Adaptive Methods for Aggregated Domain Generalizat
Explainability of the Implications of Supervised and Unsupervised Face Image Quality Estimations Through Activation Map Variation Analyses in Face Recognition Models
Explainable_FIQA_WITH_AMVA Note This is the official repository of the paper: Explainability of the Implications of Supervised and Unsupervised Face I
(AAAI2022) Style Mixing and Patchwise Prototypical Matching for One-Shot Unsupervised Domain Adaptive Semantic Segmentation
SM-PPM This is a Pytorch implementation of our paper "Style Mixing and Patchwise Prototypical Matching for One-Shot Unsupervised Domain Adaptive Seman
Official Implementation of SimIPU: Simple 2D Image and 3D Point Cloud Unsupervised Pre-Training for Spatial-Aware Visual Representations
Official Implementation of SimIPU SimIPU: Simple 2D Image and 3D Point Cloud Unsupervised Pre-Training for Spatial-Aware Visual Representations Since
The ldapconsole script allows you to perform custom LDAP requests to a Windows domain
ldapconsole The ldapconsole script allows you to perform custom LDAP requests to a Windows domain. Features Authenticate with password Authenticate wi
Domain To Api [ PYTHON ]
Domain To IP Usage You Open Terminal For Run The Program python ip.py Input & Output Input Your List e.g domain.txt Output ( For Save Output File )
Template for a rest app with flask, flask-rest and more...
Flask REST Template About the project (some comments): The ideia behind the project is to create an useful and simple template for an rest app . Besid
[CVPR 2020] Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective
Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective [Arxiv] This is PyTorch implementation of th
Conflict-aware Inference of Python Compatible Runtime Environments with Domain Knowledge Graph, ICSE 2022
PyCRE Conflict-aware Inference of Python Compatible Runtime Environments with Domain Knowledge Graph, ICSE 2022 Dependencies This project is developed
Takes a file of hosts or domains and outputs the IP address of each host/domain in the file.
Takes a file of hosts or domains and outputs the IP address of each host/domain in the file. Installation $ git clone https://github.com/whoamisec75/i
DOP-Tuning(Domain-Oriented Prefix-tuning model)
DOP-Tuning DOP-Tuning(Domain-Oriented Prefix-tuning model)代码基于Prefix-Tuning改进. Files ├── seq2seq # Code for encoder-decoder arch
Interactive Visualization to empower domain experts to align ML model behaviors with their knowledge.
An interactive visualization system designed to helps domain experts responsibly edit Generalized Additive Models (GAMs). For more information, check
Unsupervised Representation Learning via Neural Activation Coding
Neural Activation Coding This repository contains the code for the paper "Unsupervised Representation Learning via Neural Activation Coding" published
Code for our work "Activation to Saliency: Forming High-Quality Labels for Unsupervised Salient Object Detection".
A2S-USOD Code for our work "Activation to Saliency: Forming High-Quality Labels for Unsupervised Salient Object Detection". Code will be released upon
This script aims to make the dynamic public ip of your local server, public.
EZ DDNS CLOUDFLARE This script aims to make the dynamic ip of your local server, public. It does this by regularly updating cloudflare's dns record. B
Unsupervised Image to Image Translation with Generative Adversarial Networks
Unsupervised Image to Image Translation with Generative Adversarial Networks Paper: Unsupervised Image to Image Translation with Generative Adversaria
Gym-TORCS is the reinforcement learning (RL) environment in TORCS domain with OpenAI-gym-like interface.
Gym-TORCS Gym-TORCS is the reinforcement learning (RL) environment in TORCS domain with OpenAI-gym-like interface. TORCS is the open-rource realistic
Official implementation for “Unsupervised Low-Light Image Enhancement via Histogram Equalization Prior”
Unsupervised Low-Light Image Enhancement via Histogram Equalization Prior. The code will release soon. Implementation Python3 PyTorch=1.0 NVIDIA GPU+
[NeurIPS 2021] ORL: Unsupervised Object-Level Representation Learning from Scene Images
Unsupervised Object-Level Representation Learning from Scene Images This repository contains the official PyTorch implementation of the ORL algorithm
Code for "Long-tailed Distribution Adaptation"
Long-tailed Distribution Adaptation (Accepted in ACM MM2021) This project is built upon BBN. Installation pip install -r requirements.txt Usage Traini
Reference implementation for Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Diffusion Probabilistic Models This repository provides a reference implementation of the method described in the paper: Deep Unsupervised Learning us
Pytorch domain library for recommendation systems
TorchRec (Experimental Release) TorchRec is a PyTorch domain library built to provide common sparsity & parallelism primitives needed for large-scale
Answering Open-Domain Questions of Varying Reasoning Steps from Text
This repository contains the authors' implementation of the Iterative Retriever, Reader, and Reranker (IRRR) model in the EMNLP 2021 paper "Answering Open-Domain Questions of Varying Reasoning Steps from Text".
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
TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation
TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation Zhaoyun Yin, Pichao Wang, Fan Wang, Xianzhe Xu, Hanling Zhang, Hao Li
TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation
TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation Zhaoyun Yin, Pichao Wang, Fan Wang, Xianzhe Xu, Hanling Zhang, Hao Li
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
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
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
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
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
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
clustimage is a python package for unsupervised clustering of images.
clustimage The aim of clustimage is to detect natural groups or clusters of images. Image recognition is a computer vision task for identifying and ve
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
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
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
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
Pytorch implementation for "Implicit Semantic Response Alignment for Partial Domain Adaptation"
Implicit-Semantic-Response-Alignment Pytorch implementation for "Implicit Semantic Response Alignment for Partial Domain Adaptation" Prerequisites pyt
Adversarial Reweighting for Partial Domain Adaptation
Adversarial Reweighting for Partial Domain Adaptation Code for paper "Xiang Gu, Xi Yu, Yan Yang, Jian Sun, Zongben Xu, Adversarial Reweighting for Par
Domain Adaptation with Invariant RepresentationLearning: What Transformations to Learn?
Domain Adaptation with Invariant RepresentationLearning: What Transformations to Learn? Repository Structure: DSAN |└───amazon | └── dataset (Amazo
Balancing Principle for Unsupervised Domain Adaptation
Blancing Principle for Domain Adaptation NeurIPS 2021 Paper Abstract We address the unsolved algorithm design problem of choosing a justified regulari
[NIPS 2021] UOTA: Improving Self-supervised Learning with Automated Unsupervised Outlier Arbitration.
UOTA: Improving Self-supervised Learning with Automated Unsupervised Outlier Arbitration This repository is the official PyTorch implementation of UOT
StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators
StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators [Project Website] [Replicate.ai Project] StyleGAN-NADA: CLIP-Guided Domain Adaptation
Official Pytorch Implementation of Unsupervised Image Denoising With Frequency Domain Knowledge (BMVC2021 Oral Accepted Paper)
Unsupervised Image Denoising with Frequency Domain Knowledge (BMVC 2021 Oral) : Official Project Page This repository provides the official PyTorch im
A multi-scale unsupervised learning for deformable image registration
A multi-scale unsupervised learning for deformable image registration Shuwei Shao, Zhongcai Pei, Weihai Chen, Wentao Zhu, Xingming Wu and Baochang Zha
Official Pytorch Implementation of Unsupervised Image Denoising with Frequency Domain Knowledge
Unsupervised Image Denoising with Frequency Domain Knowledge (BMVC 2021 Oral) : Official Project Page This repository provides the official PyTorch im
SPCL: A New Framework for Domain Adaptive Semantic Segmentation via Semantic Prototype-based Contrastive Learning
SPCL SPCL: A New Framework for Domain Adaptive Semantic Segmentation via Semantic Prototype-based Contrastive Learning Update on 2021/11/25: ArXiv Ver
Unsupervised Feature Ranking via Attribute Networks.
FRANe Unsupervised Feature Ranking via Attribute Networks (FRANe) converts a dataset into a network (graph) with nodes that correspond to the features
PyTorch implementation of CDistNet: Perceiving Multi-Domain Character Distance for Robust Text Recognition
PyTorch implementation of CDistNet: Perceiving Multi-Domain Character Distance for Robust Text Recognition The unofficial code of CDistNet. Now, we ha
A simple dork generator written in python that outputs dorks with the domain extensions you enter
Dork Gen A simple dork generator written in python that outputs dorks with the domain extensions you enter in a ".txt file". Usage The code is pretty
CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system
CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system
「📖」Tool created to extract metadata from a domain
Metafind is an OSINT tool created with the aim of automating the search for metadata of a particular domain from the search engine known as Google.
Code of TVT: Transferable Vision Transformer for Unsupervised Domain Adaptation
TVT Code of TVT: Transferable Vision Transformer for Unsupervised Domain Adaptation Datasets: Digit: MNIST, SVHN, USPS Object: Office, Office-Home, Vi
Training code and evaluation benchmarks for the "Self-Supervised Policy Adaptation during Deployment" paper.
Self-Supervised Policy Adaptation during Deployment PyTorch implementation of PAD and evaluation benchmarks from Self-Supervised Policy Adaptation dur
Code for Paper Predicting Osteoarthritis Progression via Unsupervised Adversarial Representation Learning
Predicting Osteoarthritis Progression via Unsupervised Adversarial Representation Learning (c) Tianyu Han and Daniel Truhn, RWTH Aachen University, 20
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations Code repo for paper Trans-Encoder: Unsupervised sentence-pa
Repo for our ICML21 paper Unsupervised Learning of Visual 3D Keypoints for Control
Unsupervised Learning of Visual 3D Keypoints for Control [Project Website] [Paper] Boyuan Chen1, Pieter Abbeel1, Deepak Pathak2 1UC Berkeley 2Carnegie
A modular domain adaptation library written in PyTorch.
A modular domain adaptation library written in PyTorch.
Domain Generalization for Mammography Detection via Multi-style and Multi-view Contrastive Learning
MSVCL_MICCAI2021 Installation Please follow the instruction in pytorch-CycleGAN-and-pix2pix to install. Example Usage An example of vendor-styles tran
Backdoor Attack through Frequency Domain
Backdoor Attack through Frequency Domain DEPENDENCIES python==3.8.3 numpy==1.19.4 tensorflow==2.4.0 opencv==4.5.1 idx2numpy==1.2.3 pytorch==1.7.0 Data
cleanlab is the data-centric ML ops package for machine learning with noisy labels.
cleanlab is the data-centric ML ops package for machine learning with noisy labels. cleanlab cleans labels and supports finding, quantifying, and lear
DivNoising is an unsupervised denoising method to generate diverse denoised samples for any noisy input image. This repository contains the code to reproduce the results reported in the paper https://openreview.net/pdf?id=agHLCOBM5jP
DivNoising: Diversity Denoising with Fully Convolutional Variational Autoencoders Mangal Prakash1, Alexander Krull1,2, Florian Jug2 1Authors contribut
A Domain-Agnostic Benchmark for Self-Supervised Learning
DABS: A Domain Agnostic Benchmark for Self-Supervised Learning This repository contains the code for DABS, a benchmark for domain-agnostic self-superv
Uma versão em Python/Ursina do aplicativo Real Drum (android).
Real Drum Descrição Esta é uma versão alternativa feita em Python com a engine Ursina do aplicatio Real Drum (presente no Google Play Store). Como exe
Code release for Universal Domain Adaptation(CVPR 2019)
Universal Domain Adaptation Code release for Universal Domain Adaptation(CVPR 2019) Requirements python 3.6+ PyTorch 1.0 pip install -r requirements.t
VR-Caps: A Virtual Environment for Active Capsule Endoscopy
VR-Caps: A Virtual Environment for Capsule Endoscopy Overview We introduce a virtual active capsule endoscopy environment developed in Unity that prov
Current state of supervised and unsupervised depth completion methods
Awesome Depth Completion Table of Contents About Sparse-to-Dense Depth Completion Current State of Depth Completion Unsupervised VOID Benchmark Superv
Create beautiful diagrams just by typing mathematical notation in plain text.
Penrose Penrose is an early-stage system that is still in development. Our system is not ready for contributions or public use yet, but hopefully will
[AAAI2021] The source code for our paper 《Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion》.
DSM The source code for paper Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion Project Website; Datasets li
The code for Bi-Mix: Bidirectional Mixing for Domain Adaptive Nighttime Semantic Segmentation
BiMix The code for Bi-Mix: Bidirectional Mixing for Domain Adaptive Nighttime Semantic Segmentation arxiv Framework: visualization results: Requiremen
The source code and dataset for the RecGURU paper (WSDM 2022)
RecGURU About The Project Source code and baselines for the RecGURU paper "RecGURU: Adversarial Learning of Generalized User Representations for Cross
ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation
ClevrTex This repository contains dataset generation code for ClevrTex benchmark from paper: ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi
UNAVOIDS: Unsupervised and Nonparametric Approach for Visualizing Outliers and Invariant Detection Scoring
UNAVOIDS: Unsupervised and Nonparametric Approach for Visualizing Outliers and Invariant Detection Scoring Code Summary aggregate.py: this script aggr
An Unsupervised Detection Framework for Chinese Jargons in the Darknet
An Unsupervised Detection Framework for Chinese Jargons in the Darknet This repo is the Python 3 implementation of 《An Unsupervised Detection Framewor
Unsupervised clustering of high content screen samples
Microscopium Unsupervised clustering and dataset exploration for high content screens. See microscopium in action Public dataset BBBC021 from the Broa
Use unsupervised and supervised learning to predict stocks
AIAlpha: Multilayer neural network architecture for stock return prediction This project is meant to be an advanced implementation of stacked neural n
Flappy bird automation using Neuroevolution of Augmenting Topologies (NEAT) in Python
FlappyAI Flappy bird automation using Neuroevolution of Augmenting Topologies (NEAT) in Python Everything Used Genetic Algorithm especially NEAT conce
This project uses unsupervised machine learning to identify correlations between daily inoculation rates in the USA and twitter sentiment in regards to COVID-19.
Twitter COVID-19 Sentiment Analysis Members: Christopher Bach | Khalid Hamid Fallous | Jay Hirpara | Jing Tang | Graham Thomas | David Wetherhold Pro
[ArXiv 2021] One-Shot Generative Domain Adaptation
GenDA - One-Shot Generative Domain Adaptation One-Shot Generative Domain Adaptation Ceyuan Yang*, Yujun Shen*, Zhiyi Zhang, Yinghao Xu, Jiapeng Zhu, Z
PyTorch implementation of our ICCV 2021 paper Intrinsic-Extrinsic Preserved GANs for Unsupervised 3D Pose Transfer.
Unsupervised_IEPGAN This is the PyTorch implementation of our ICCV 2021 paper Intrinsic-Extrinsic Preserved GANs for Unsupervised 3D Pose Transfer. Ha
Visual Memorability for Robotic Interestingness via Unsupervised Online Learning (ECCV 2020 Oral and TRO)
Visual Interestingness Refer to the project description for more details. This code based on the following paper. Chen Wang, Yuheng Qiu, Wenshan Wang,
Self-attentive task GAN for space domain awareness data augmentation.
SATGAN TODO: update the article URL once published. Article about this implemention The self-attentive task generative adversarial network (SATGAN) le
Create images and texts with the First Order Generative Adversarial Networks
First Order Divergence for training GANs This repository contains code accompanying the paper First Order Generative Advesarial Netoworks The majority