darts
Architecture finder
Automated method to find optimal architecture for machine learning models
Differentiable architecture search for convolutional and recurrent networks
4k stars
86 watching
843 forks
Language: Python
last commit: about 4 years ago
Linked from 1 awesome list
automlconvolutional-networksdeep-learningimage-classificationlanguage-modelingneural-architecture-searchpytorchrecurrent-networks
weiaicunzai/awesome-image-classificationRelated projects:
| Repository | Description | Stars |
|---|---|---|
 khanrc/pt.darts | An implementation of DARTS, a method for automatically designing neural network architectures. | 443 |
 dyhan0920/pyramidnet-pytorch | An implementation of a deep neural network architecture for image classification tasks | 273 |
 ericsun99/shufflenet-v2-pytorch | A PyTorch implementation of a ShuffleNet-v2 neural network architecture for image classification. | 431 |
 carpedm20/enas-pytorch | Automates the discovery of neural network architectures by sharing parameters between subgraphs in a large computational graph | 2,709 |
 ahmedfgad/numpycnn | A Python implementation of a Convolutional Neural Network from scratch using NumPy for building CNNs from scratch | 577 |
 jhkim89/pyramidnet | A Torch implementation of a novel neural network architecture designed to improve the generalization ability of deep image classification models. | 129 |
 donnyyou/torchcv | A comprehensive PyTorch-based framework for computer vision tasks | 2,249 |
 randl/shufflenetv2-pytorch | An implementation of a lightweight convolutional neural network architecture for mobile devices | 191 |
 yunjey/pytorch-tutorial | A comprehensive tutorial project that provides code examples for learning PyTorch by implementing various deep learning models and demonstrating their usage. | 30,401 |
 xternalz/wideresnet-pytorch | An implementation of Wide Residual Networks in PyTorch for efficient deep learning on CIFAR10/100 datasets. | 334 |
 locuslab/optnet | A PyTorch module that adds differentiable optimization as a layer to neural networks | 517 |
| locuslab/tcn | An empirical evaluation of generic convolutional and recurrent networks for sequence modeling | 4,204 |
 chenxi116/pnasnet.pytorch | PyTorch implementation of PNASNet-5 architecture | 317 |
 kimhc6028/relational-networks | A PyTorch implementation of a neural network module for relational reasoning in computer vision tasks | 809 |
 ixaxaar/pytorch-dnc | An implementation of Differentiable Neural Computers and family for PyTorch, enabling scalable memory-augmented neural networks. | 338 |