awesome-domain-adaptation
transferlearning
awesome-domain-adaptation | transferlearning | |
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1 | 1 | |
4,905 | 12,880 | |
- | - | |
6.0 | 7.8 | |
about 1 month ago | 16 days ago | |
Python | ||
MIT License | MIT License |
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awesome-domain-adaptation
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Segmentation on synthetic images does not generalize on experimental data.
This is a typical problem of domain adaptation. You can look up papers related to it here: https://github.com/zhaoxin94/awesome-domain-adaptation
transferlearning
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[D] Medium Article: Adaptive Learning for Time Series Forecasting
The src is available in https://github.com/jindongwang/transferlearning I'll also publish about how to code the model for time series
What are some alternatives?
salient-extract - Salient feature extractor based on yoloV8
zshot - Zero and Few shot named entity & relationships recognition
Composite-Image-Generator - Semi-sythetic data generator using the "copy - paste" method.
stackoverflow-better-stats - Better statistics about Stack Overflow's 2023 Developer Survey
awesome-artificial-intelligence-research - A curated list of Artificial Intelligence (AI) Research, tracks the cutting edge trending of AI research, including recommender systems, computer vision, machine learning, etc.
PaddleHelix - Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集
TS-TCC - [IJCAI-21] "Time-Series Representation Learning via Temporal and Contextual Contrasting"
Transfer-Learning-Library - Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
Efficient-VDVAE - Official Pytorch and JAX implementation of "Efficient-VDVAE: Less is more"
FSL-Mate - FSL-Mate: A collection of resources for few-shot learning (FSL).
train-procgen - Code for the paper "Leveraging Procedural Generation to Benchmark Reinforcement Learning"