victorcampos7 / weightnorm-initLinks
Code for "How to Initialize your Network? Robust Initialization for WeightNorm & ResNets"
☆14Updated last year
Alternatives and similar repositories for weightnorm-init
Users that are interested in weightnorm-init are comparing it to the libraries listed below
Sorting:
- EnAET: Self-Trained Ensemble AutoEncoding Transformations for Semi-Supervised Learning☆82Updated last year
- Mean Absolute Error Does Not Treat Examples Equally and Gradient Magnitude’s Variance Matters☆30Updated 4 years ago
- Batch-Instance Normalization (BIN)☆78Updated 5 years ago
- This repository contains some of the latest data augmentation techniques and optimizers for image classification using pytorch and the CI…☆29Updated 3 years ago
- [TPAMI2022 & NeurIPS2020] Official implementation of Self-Adaptive Training☆128Updated 3 years ago
- [NeurIPS '18] "Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?" Official Implementation.☆129Updated 3 years ago
- Cheap distillation for convolutional neural networks.☆33Updated 6 years ago
- "Layer-wise Adaptive Rate Scaling" in PyTorch☆87Updated 4 years ago
- Tensorflow implementation of S4L: Self-Supervised Semi-Supervised Learning☆94Updated 5 years ago
- Record experiment data easily☆13Updated 2 years ago
- Implemenation of Semi-Supervised Learning using GANs in PyTorch for MNIST and CIFAR-10 datasets☆15Updated 6 years ago
- OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)☆62Updated last year
- This project is the Torch implementation of our accepted AAAI 2018 paper : orthogonal weight normalization method for solving orthogonali…☆57Updated 5 years ago
- Bootstrap Your Own Latent (BYOL) pytorch implementation using DistributedDataParallel.☆28Updated 2 years ago
- Improving Consistency-Based Semi-Supervised Learning with Weight Averaging☆186Updated 6 years ago
- AffinityNet with feature attention layer and kNN attention pooling layer for few-shot semi-supervised learning☆38Updated 6 years ago
- ☆42Updated 6 years ago
- Pre-trained model, code, and materials from the paper "Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmen…☆60Updated 4 years ago
- To train deep convolutional neural networks, the input data and the activations need to be kept in memory. Given the limited memory avail…☆100Updated last year
- Differentiable Data Augmentation Library☆123Updated 2 years ago
- Implementation of soft parameter sharing for neural networks☆69Updated 4 years ago
- When Does Label Smoothing Help?_pytorch_implementationimp☆124Updated 5 years ago
- PyTorch implementation of "Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning" with DDP and Apex AMP☆81Updated 4 years ago
- Code for reproducing ICT (published in Neural Networks 2022, and in IJCAI 2019)☆148Updated 2 years ago
- An official collection of code in different frameworks that reproduces experiments in "Group Normalization"☆118Updated 4 years ago
- PyTorch implementation of Weighted Batch-Normalization layers☆37Updated 4 years ago
- ☆84Updated 6 years ago
- Code for paper "Orthogonal Convolutional Neural Networks".☆116Updated 3 years ago
- Code and data of the "Multi-domain adversarial learning" paper, Schoenauer-Sebag et al., accepted at ICLR 2019☆38Updated 4 years ago
- Class Activation Map(CAM) with Pytorch☆66Updated 5 years ago