LtC-MSDA
Implementation of Learning to Combine: Knowledge Aggregation for Multi-Source Domain Adaptation (ECCV 2020).
AI summary
Domain Adaptation Framework
An implementation of a knowledge aggregation method for adapting to multiple domains using a graph-based framework.
- stars
- 69
- forks
- 16
- watching
- 6
- awesome list
- 1
Similar projects
Found by comparing what the projects do, not just their names.
lhoyer/hrda236
Domain Adaptation Framework
A framework for unsupervised domain adaptation in semantic segmentation using multi-resolution training and learned scale attention.
Domain adaptation toolkit
A toolbox for comparing and running domain adaptation algorithms on different datasets.
Domain adaptation software
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.
Domain adaptation library
A collection of implementations of algorithms to adapt deep learning models from one domain to another
Domain adaptation model
This project implements a deep learning-based approach to adapt semantic segmentation models from one domain to another.
Domain adaptation algorithm
Develops object detection algorithms to adapt to new domains with limited supervision
Domain adaptation
Improves federated learning performance by incorporating domain knowledge and regularization to adapt models across diverse domains
Context-aware adaptor
An unsupervised domain adaptation method that uses contextual information to improve performance on visual recognition tasks
Task adaptation framework
Adapting a single network to multiple tasks by learning to mask weights
Architecture adapter
An approach to improve neural architecture search by adapting architectures between domains to improve generalization performance on new datasets.
Point Cloud Adapter
Develops a deep learning model for domain adaptation on 3D point cloud data
Domain generalization method
This project presents a method for federated domain generalization with adjustment, allowing multiple models to learn from each other across different domains.
Concreteness estimator
Automatically generates concreteness estimates for languages using pre-trained semantic models and linear regression
Memory optimizer
A JAX transform that simplifies the training of large language models by reducing memory usage through low-rank adaptation.
Climate data engine
A Python toolkit for accessing and analyzing climate data from the Cal-Adapt Analytics Engine.
Featured in 1 awesome list
Each link jumps to the spot where the list mentions LtC-MSDA.
