timgaripov / swaLinks
Stochastic Weight Averaging in PyTorch
☆974Updated 3 years ago
Alternatives and similar repositories for swa
Users that are interested in swa are comparing it to the libraries listed below
Sorting:
- lookahead optimizer (Lookahead Optimizer: k steps forward, 1 step back) for pytorch☆335Updated 5 years ago
- mixup: Beyond Empirical Risk Minimization☆1,180Updated 3 years ago
- Efficient Learning of Augmentation Policy Schedules☆507Updated 5 years ago
- Implementations of ideas from recent papers☆393Updated 4 years ago
- 2.56%, 15.20%, 1.30% on CIFAR10, CIFAR100, and SVHN https://arxiv.org/abs/1708.04552☆549Updated 5 years ago
- AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty☆989Updated last month
- ☆1,139Updated 2 years ago
- Implementation of the mixup training method☆466Updated 6 years ago
- A New Optimization Technique for Deep Neural Networks☆538Updated 3 years ago
- Code for Noisy Student Training. https://arxiv.org/abs/1911.04252☆761Updated 4 years ago
- Over9000 optimizer☆426Updated 2 years ago
- Code for Switchable Normalization from "Differentiable Learning-to-Normalize via Switchable Normalization", https://arxiv.org/abs/1806.10…☆866Updated 4 years ago
- Fine-tune pretrained Convolutional Neural Networks with PyTorch☆723Updated 9 months ago
- Code for reproducing Manifold Mixup results (ICML 2019)☆494Updated last year
- A PyTorch implementation of " EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks."☆313Updated 5 years ago
- Open source release of the evaluation benchmark suite described in "Realistic Evaluation of Deep Semi-Supervised Learning Algorithms"☆460Updated 5 years ago
- Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"☆798Updated last year
- Standardizing weights to accelerate micro-batch training☆548Updated 3 years ago
- Pytorch implementation for "Large-Scale Long-Tailed Recognition in an Open World" (CVPR 2019 ORAL)☆863Updated 2 years ago
- Scaling and Benchmarking Self-Supervised Visual Representation Learning☆586Updated 3 years ago
- Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019☆611Updated 3 years ago
- PyTorch Implementation for Deep Metric Learning Pipelines☆573Updated 4 years ago
- Best CIFAR-10, CIFAR-100 results with wide-residual networks using PyTorch☆470Updated 5 years ago
- Gradually-Warmup Learning Rate Scheduler for PyTorch☆988Updated 7 months ago
- Unsupervised Feature Learning via Non-parametric Instance Discrimination☆753Updated 4 years ago
- Public repo for Augmented Multiscale Deep InfoMax representation learning☆400Updated 4 years ago
- Deep Learning Experiment Management☆639Updated 2 years ago
- Wide Residual Networks (WideResNets) in PyTorch☆338Updated 4 years ago
- Implementation of DropBlock: A regularization method for convolutional networks in PyTorch.☆596Updated 4 years ago
- Ranger - a synergistic optimizer using RAdam (Rectified Adam), Gradient Centralization and LookAhead in one codebase☆1,201Updated last year