davidcpage / cifar10-fast
☆536Updated 3 years ago
Alternatives and similar repositories for cifar10-fast:
Users that are interested in cifar10-fast are comparing it to the libraries listed below
- ☆304Updated 4 years ago
- Efficient Learning of Augmentation Policy Schedules☆505Updated 5 years ago
- Implementations of ideas from recent papers☆392Updated 4 years ago
- Library for faster pinned CPU <-> GPU transfer in Pytorch☆685Updated 5 years ago
- Standardizing weights to accelerate micro-batch training☆547Updated 3 years ago
- Over9000 optimizer☆427Updated 2 years ago
- PyTorch layer-by-layer model profiler☆606Updated 3 years ago
- ConvNet training using pytorch☆345Updated 4 years ago
- Sparse learning library and sparse momentum resources.☆380Updated 2 years ago
- Compute receptive fields of your favorite convnets☆439Updated 3 years ago
- Code for: "And the bit goes down: Revisiting the quantization of neural networks"☆633Updated 4 years ago
- A PyTorch implementation of " EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks."☆311Updated 5 years ago
- Weakly Supervised Learning On Images☆601Updated 3 years ago
- Code snippets created for the PyTorch discussion board☆561Updated 4 years ago
- Experimental ground for optimizing memory of pytorch models☆366Updated 6 years ago
- Tutorial for building a custom CUDA function for Pytorch☆511Updated 6 years ago
- A plug-in replacement for DataLoader to load Imagenet disk-sequentially in PyTorch.☆238Updated 3 years ago
- This repository reproduces the results of the paper: "Fixing the train-test resolution discrepancy" https://arxiv.org/abs/1906.06423☆1,040Updated 3 years ago
- AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty☆984Updated last week
- Gradient based receptive field estimation for Convolutional Neural Networks☆338Updated 5 years ago
- 🔥 Reproducibly benchmarking Keras and PyTorch models☆367Updated 4 years ago
- Stochastic Weight Averaging in PyTorch☆969Updated 3 years ago
- torchbearer: A model fitting library for PyTorch☆639Updated last year
- Discover augmentation strategies tailored for your dataset☆249Updated 4 years ago
- Scaling and Benchmarking Self-Supervised Visual Representation Learning☆586Updated 3 years ago
- 2.56%, 15.20%, 1.30% on CIFAR10, CIFAR100, and SVHN https://arxiv.org/abs/1708.04552☆551Updated 5 years ago
- A drop-in replacement for CIFAR-10.☆240Updated 4 years ago
- Memory consumption and FLOP count estimates for convnets☆918Updated 6 years ago
- Deal with bad samples in your dataset dynamically, use Transforms as Filters, and more!☆377Updated 2 years ago
- A large scale study of Knowledge Distillation.☆220Updated 4 years ago