Transfer-Learning-Library
transferlearning
Transfer-Learning-Library | transferlearning | |
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1 | 1 | |
3,150 | 12,867 | |
2.2% | - | |
6.9 | 7.8 | |
about 1 month ago | 9 days ago | |
Python | Python | |
MIT License | MIT License |
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Transfer-Learning-Library
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[R] pytorch library for audio/speech domain adaptation?
Are there any pytorch libraries to do benchmarking of domain adaptation methods for audio/speech tasks? Something like the Transfer Learning Library (https://github.com/thuml/Transfer-Learning-Library/) for images.
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?
TranAD - [VLDB'22] Anomaly Detection using Transformers, self-conditioning and adversarial training.
zshot - Zero and Few shot named entity & relationships recognition
DeepLabCut - Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
stackoverflow-better-stats - Better statistics about Stack Overflow's 2023 Developer Survey
CEPC - A domain adaptation model
PaddleHelix - Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集
AdaTime - [TKDD 2023] AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data
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.
StyleDomain - Official Implementation for "StyleDomain: Efficient and Lightweight Parameterizations of StyleGAN for One-shot and Few-shot Domain Adaptation" (ICCV 2023)
TS-TCC - [IJCAI-21] "Time-Series Representation Learning via Temporal and Contextual Contrasting"
pytorch-adapt - Domain adaptation made easy. Fully featured, modular, and customizable.
Efficient-VDVAE - Official Pytorch and JAX implementation of "Efficient-VDVAE: Less is more"