Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning deep-learningone-shot-learningmeta-learningfew-shot-learninglearning-to-learn UpdatedNov 26, 2018 tristandeleu/pytorch-meta Star2k A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTor...
This is OfficialPyTorch implementationfor HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning. @inproceedings{lee2021help, title = {HELP: Hardware-Adaptive Efficient Latency Prediction for NAS via Meta-Learning}, author = {Lee, Hayeon and Lee, Sewoong and Chong, Song and...
Pytorch Code:dragen1860/MAML-Pytorch 或katerakelly/pytorch-maml Tensorflow Code:cbfinn/maml Berkeley的 Finn 在meta-learning领域创造了很多开创性的成果,尤其是在meta-reinforcement learning in robotics方面,以后会详细讲解这方面的成果。 Model-Agnostic Meta-Learning (Finn, et al. 2017) 是一个非常通用的opt...
有哪些比较好的元学习(meta learning)领域的学习资源? 徐致国 大部分自然科学都会一丁点,少部分一窍不通 在这里推荐一个库吧: 一般元学习编程中的痛点之一就是要手撸模型,因为pytorch本身要求模型的参数都是叶子结点,不能继续求导运算。 这个库实现了一个叫… ...
项目需要安装python 3.8及以上版本，pytorch 1.7及以上版本和torchvision 0.8及以上版本。此外，作者强烈建议安装支持CUDA的PyTorch和TorchVision。安装Segment Anything：python -m pip install -e segment_anything 安装GroundingDINO：python -m pip install -e GroundingDINO 安装diffusers：pip install --upgrade ...
The video tutorial can be found from:Model Agnostic Meta Learning Related Videos:My talk for Model Agnostic Meta Learning with domain adaptation Paper:https://arxiv.org/pdf/1703.03400.pdf pyTorch Implementation: 1.https://github.com/dragen1860/MAML-Pytorch ...
论文:《MAML: ModelAgnostic Meta Learning》 论文地址:https://arxiv.org/pdf/1703.03400.pdf github:httpshttps://github.com/dragen1860/MAML-Pytorch 一、算法原理 将数据集分成meta-train和meta-test两部分,meta-test测试模型的收敛速度(用Dtrain训练,用Dtest测试分类效果),meta-train用于训练模型(Dtrain和Dte...
除了用随机数,也可以用预训练的网络参数来初始化神经网络,也就是所谓 transfer learning,或者更准确地说是 fine-tuning 的技术。如果不了解 fine-tuning 技术,可以阅读这篇博客: Building powerful image classification models using very little data, 地址链接...
On software packages for meta-learningA lot of research code releases (code is fragile and sometimes broken) A few notable libraries that implement a few specific methods: Torchmeta (https://github.com/tristandeleu/pytorch-meta) Learn2learn (https://github.com/learnables/learn2learn) ...
例如，让 Llama 2 对使用 PyTorch 的利弊问题创建更有针对性的技术回答：complete_and_print ("Explain the pros and cons of using PyTorch.")# More likely to explain the pros and cons of PyTorch covers general areas like documentation, the PyTorch community, and mentions a steep learning curve...