noahfl / densenet-sdr
repo that holds code for improving on dropout using Stochastic Delta Rule
☆142Updated 6 years ago
Alternatives and similar repositories for densenet-sdr:
Users that are interested in densenet-sdr are comparing it to the libraries listed below
- Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.☆77Updated 6 years ago
- A TensorFlow implementation of Group Normalization on the task of image classification☆208Updated 6 years ago
- Code used to generate the results appearing in "Train longer, generalize better: closing the generalization gap in large batch training o…☆149Updated 7 years ago
- Reference caffe implementation of LSUV initialization☆112Updated 7 years ago
- A PyTorch implementation of the paper Mixup: Beyond Empirical Risk Minimization in PyTorch☆123Updated 7 years ago
- PyTorch implementation of a deep metric learning technique called "Magnet Loss" from Facebook AI Research (FAIR) in ICLR 2016.☆220Updated last year
- Implementation of "Learning with Random Learning Rates" in PyTorch.☆102Updated 5 years ago
- ICLR 2018 reproducibility challenge - Multi-Scale Dense Convolutional Networks for Efficient Prediction☆135Updated 6 years ago
- auto-tuning momentum SGD optimizer☆286Updated 5 years ago
- visualization of CNN in PyTorch☆155Updated last year
- TensorFlow implementation of PNASNet-5 on ImageNet☆101Updated 6 years ago
- Complementary code for the Targeted Dropout paper☆255Updated 5 years ago
- ☆138Updated 8 years ago
- [ECCV 2018] Sparsely Aggreagated Convolutional Networks https://arxiv.org/abs/1801.05895☆124Updated 6 years ago
- A pytorch implementation of "Self-Normalizing Neural Networks" by Klambauer et al. (still beta)☆59Updated 7 years ago
- PyTorch implementation of CVPR'18 - Perturbative Neural Networks http://xujuefei.com/pnn.html☆138Updated 6 years ago
- Files to create the figures in the paper "Super-Convergence: Very Fast Training of Residual Networks Using Large Learning Rates"☆191Updated 7 years ago
- Label Refinery: Improving ImageNet Classification through Label Progression☆279Updated 6 years ago
- Utilities for Pytorch☆89Updated 2 years ago
- Using the CLR algorithm for training (https://arxiv.org/abs/1506.01186)☆108Updated 6 years ago
- Second-order optimiser for deep networks☆76Updated 6 years ago
- 2.86% and 15.85% on CIFAR-10 and CIFAR-100☆296Updated 6 years ago
- Deformable Convolutional Networks + MST + Soft-NMS☆234Updated 7 years ago
- ☆251Updated 8 years ago
- Compare outputs between layers written in Tensorflow and layers written in Pytorch☆72Updated 6 years ago
- PyTorch implementation of Wide Residual Networks with 1-bit weights by McDonnell (ICLR 2018)☆124Updated 6 years ago
- This is an example of how to train a MNIST network in Python and run it in c++ with pytorch 1.0☆96Updated 6 years ago
- Pytorch implementation of MaxPoolingLoss.☆175Updated 6 years ago
- Corrupted labels and label smoothing☆128Updated 7 years ago
- A new kind of pooling layer for faster and sharper convergence☆76Updated 7 years ago