timgaripov / swa
Stochastic Weight Averaging in PyTorch
☆969Updated 3 years ago
Alternatives and similar repositories for swa:
Users that are interested in swa are comparing it to the libraries listed below
- Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"☆792Updated last year
- Implementations of ideas from recent papers☆392Updated 4 years ago
- AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty☆984Updated this week
- mixup: Beyond Empirical Risk Minimization☆1,177Updated 3 years ago
- Official Implementation of 'Fast AutoAugment' in PyTorch.☆1,601Updated 3 years ago
- A New Optimization Technique for Deep Neural Networks☆535Updated 3 years ago
- lookahead optimizer (Lookahead Optimizer: k steps forward, 1 step back) for pytorch☆334Updated 5 years ago
- 2.56%, 15.20%, 1.30% on CIFAR10, CIFAR100, and SVHN https://arxiv.org/abs/1708.04552☆551Updated 5 years ago
- Unofficial implementation of the ImageNet, CIFAR 10 and SVHN Augmentation Policies learned by AutoAugment using pillow☆1,480Updated last year
- Over9000 optimizer☆427Updated 2 years ago
- Ranger - a synergistic optimizer using RAdam (Rectified Adam), Gradient Centralization and LookAhead in one codebase☆1,197Updated last year
- A PyTorch implementation of " EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks."☆310Updated 5 years ago
- Efficient Learning of Augmentation Policy Schedules☆505Updated 5 years ago
- Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019☆609Updated 3 years ago
- Best CIFAR-10, CIFAR-100 results with wide-residual networks using PyTorch☆465Updated 5 years ago
- 🛠 Toolbox to extend PyTorch functionalities☆418Updated 10 months ago
- Implementation of the mixup training method☆466Updated 6 years ago
- Scaling and Benchmarking Self-Supervised Visual Representation Learning☆585Updated 3 years ago
- Implementation of DropBlock: A regularization method for convolutional networks in PyTorch.☆593Updated 4 years ago
- PyTorch Implementation for Deep Metric Learning Pipelines☆572Updated 4 years ago
- Pytorch implementation for "Large-Scale Long-Tailed Recognition in an Open World" (CVPR 2019 ORAL)☆856Updated 2 years ago
- Wide Residual Networks (WideResNets) in PyTorch☆337Updated 3 years ago
- Standardizing weights to accelerate micro-batch training☆547Updated 3 years ago
- Code for Switchable Normalization from "Differentiable Learning-to-Normalize via Switchable Normalization", https://arxiv.org/abs/1806.10…☆865Updated 4 years ago
- This repository reproduces the results of the paper: "Fixing the train-test resolution discrepancy" https://arxiv.org/abs/1906.06423☆1,039Updated 3 years ago
- Code for reproducing Manifold Mixup results (ICML 2019)☆487Updated 11 months ago
- Pretrained bag-of-local-features neural networks☆312Updated 5 years ago
- Fine-tune pretrained Convolutional Neural Networks with PyTorch☆723Updated 7 months ago
- PyTorch re-implementation of Grad-CAM (+ vanilla/guided backpropagation, deconvnet, and occlusion sensitivity maps)☆796Updated 5 years ago
- Code for Noisy Student Training. https://arxiv.org/abs/1911.04252☆759Updated 4 years ago