deep-transfer-learning

Domain adaptation library

A collection of implementations of algorithms to adapt deep learning models from one domain to another

A collection of implementations of deep domain adaptation algorithms

GitHub

892 stars
9 watching
205 forks
Language: Python
last commit: over 2 years ago
Linked from 1 awesome list

deep-transfer-learningdomain-adaptationpytorchtransfer-learning

Backlinks from these awesome lists:

Related projects:

Repository Description Stars
domainadaptation/salad A toolbox for comparing and running domain adaptation algorithms on different datasets. 333
wasidennis/adaptsegnet This project implements a deep learning-based approach to adapt semantic segmentation models from one domain to another. 849
chrisallenming/ltc-msda An implementation of a knowledge aggregation method for adapting to multiple domains using a graph-based framework. 68
amzn/xfer A collection of libraries and frameworks for transfer learning and meta-learning in deep neural networks 252
wenkehuang/rethinkfl Improves federated learning performance by incorporating domain knowledge and regularization to adapt models across diverse domains 91
deepset-ai/farm An open-source framework for adapting representation models to various tasks and industries 1,741
bupt-ai-cz/meta-selflearning Develops a method to improve performance of computer vision tasks by adapting models to new domains and data sources through meta-learning and self-learning techniques. 199
naoto0804/cross-domain-detection Develops object detection algorithms to adapt to new domains with limited supervision 422
lhoyer/hrda A framework for unsupervised domain adaptation in semantic segmentation using multi-resolution training and learned scale attention. 235
baowenxuan/atp An implementation of adaptive test-time personalization for federated learning in deep neural networks. 16
tdeboissiere/deeplearningimplementations A collection of implementations of recent deep learning papers in Python 1,815
zhanghang1989/pytorch-encoding A Python framework for building deep learning models with optimized encoding layers and batch normalization. 2,041
yerevann/warp An approach to transfer learning for NLP tasks using adversarial reprogramming and word-level task-specific embeddings. 83
vict0rsch/deep_learning A collection of tutorials and resources on implementing deep learning models using Python libraries such as Keras and Lasagne. 426
yunjey/domain-transfer-network Generates images from one domain into another without paired data using a neural network model 862