timgaripov / swaLinks
Stochastic Weight Averaging in PyTorch
☆977Updated 4 years ago
Alternatives and similar repositories for swa
Users that are interested in swa are comparing it to the libraries listed below
Sorting:
- 2.56%, 15.20%, 1.30% on CIFAR10, CIFAR100, and SVHN https://arxiv.org/abs/1708.04552☆554Updated 5 years ago
- mixup: Beyond Empirical Risk Minimization☆1,197Updated 4 years ago
- Implementations of ideas from recent papers☆392Updated 4 years ago
- lookahead optimizer (Lookahead Optimizer: k steps forward, 1 step back) for pytorch☆337Updated 6 years ago
- Over9000 optimizer☆424Updated 3 years ago
- Efficient Learning of Augmentation Policy Schedules☆508Updated 6 years ago
- A New Optimization Technique for Deep Neural Networks☆541Updated 3 years ago
- AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty☆987Updated 6 months ago
- Unofficial implementation of the ImageNet, CIFAR 10 and SVHN Augmentation Policies learned by AutoAugment using pillow☆1,494Updated 2 years ago
- Code snippets created for the PyTorch discussion board☆570Updated 4 years ago
- Standardizing weights to accelerate micro-batch training☆551Updated 3 years ago
- This repository reproduces the results of the paper: "Fixing the train-test resolution discrepancy" https://arxiv.org/abs/1906.06423☆1,045Updated 4 years ago
- ☆535Updated 3 years ago
- Ranger - a synergistic optimizer using RAdam (Rectified Adam), Gradient Centralization and LookAhead in one codebase☆1,208Updated last year
- Official Implementation of 'Fast AutoAugment' in PyTorch.☆1,609Updated 4 years ago
- Fine-tune pretrained Convolutional Neural Networks with PyTorch☆724Updated last year
- ☆1,145Updated 2 years ago
- Best CIFAR-10, CIFAR-100 results with wide-residual networks using PyTorch☆478Updated 5 years ago
- Implementation of DropBlock: A regularization method for convolutional networks in PyTorch.☆596Updated 5 years ago
- Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"☆802Updated last year
- A PyTorch implementation of " EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks."☆313Updated 5 years ago
- Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019☆613Updated 4 years ago
- Weakly Supervised Learning On Images☆602Updated 4 years ago
- Gradually-Warmup Learning Rate Scheduler for PyTorch☆993Updated last year
- Code for reproducing Manifold Mixup results (ICML 2019)☆495Updated last year
- Code for Switchable Normalization from "Differentiable Learning-to-Normalize via Switchable Normalization", https://arxiv.org/abs/1806.10…☆870Updated 5 years ago
- Pytorch implementation for "Large-Scale Long-Tailed Recognition in an Open World" (CVPR 2019 ORAL)☆866Updated 3 years ago
- Code for Noisy Student Training. https://arxiv.org/abs/1911.04252☆765Updated 4 years ago
- Visualization toolkit for neural networks in PyTorch! Demo -->☆744Updated 2 years ago
- High-level batteries-included neural network training library for Pytorch☆403Updated 3 years ago