LeungSamWai / Drop-ActivationLinks
The official implementation of paper "Drop-Activation: Implicit Parameter Reduction and Harmonious Regularization".
☆10Updated 6 years ago
Alternatives and similar repositories for Drop-Activation
Users that are interested in Drop-Activation are comparing it to the libraries listed below
Sorting:
- The implementation of paper ''Efficient Attention Network: Accelerate Attention by Searching Where to Plug''.☆20Updated 2 years ago
- Official Implementation of Convolutional Normalization: Improving Robustness and Training for Deep Neural Networks☆30Updated 3 years ago
- Compressing Representations for Self-Supervised Learning☆78Updated 4 years ago
- Robust Optimal Transport code☆43Updated 3 years ago
- This project is the Torch implementation of our accepted CVPR 2019 paper, Iterative Normalization: Beyond Standardization towards Effic…☆25Updated 4 years ago
- [NeurIPS 2020] "Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free" by Haotao Wang*, Tianlong C…☆44Updated 3 years ago
- Multi-Domain Image-to-Image Translation using StarGAN with Max Sliced Wasserstein Distance.☆14Updated 6 years ago
- Code accompanying the NeurIPS 2020 submission "Teaching a GAN What Not to Learn."☆32Updated 4 years ago
- Code for our paper "On Out-of-distribution detection with Energy-based Models" accepted to the ICML 2021 Workshop on Uncertainty & Robus…☆20Updated 4 years ago
- Regularizing Meta-Learning via Gradient Dropout☆53Updated 5 years ago
- This is the pytorch re-implementation of the IterNorm☆41Updated 6 years ago
- [CVPR 2021] "The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models" Tianlong Chen, Jon…☆68Updated 2 years ago
- ICLR 2021, Fair Mixup: Fairness via Interpolation☆57Updated 4 years ago
- ☆42Updated 5 years ago
- ☆10Updated last year
- Paper and Code for "Curriculum Learning by Optimizing Learning Dynamics" (AISTATS 2021)☆19Updated 4 years ago
- ☆44Updated 4 years ago
- Minimum viable code for the Decodable Information Bottleneck paper. Pytorch Implementation.☆11Updated 5 years ago
- ☆29Updated 5 years ago
- Repo for the paper "Extrapolating from a Single Image to a Thousand Classes using Distillation"☆37Updated last year
- [NeurIPS 2020 Oral] Is normalization indispensable for training deep neural networks?☆34Updated 3 years ago
- Code for ICLR 2022 Paper, "Controlling Directions Orthogonal to a Classifier"☆35Updated 2 years ago
- Implementation "Adapting Auxiliary Losses Using Gradient Similarity" article☆32Updated 6 years ago
- Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]☆89Updated 4 years ago
- Official repository for Reliable Label Bootstrapping☆19Updated 2 years ago
- ☆27Updated 2 years ago
- ICML'20: SIGUA: Forgetting May Make Learning with Noisy Labels More Robust☆17Updated 4 years ago
- PyTorch and Torch implementation for our accepted CVPR 2020 paper (Oral): Controllable Orthogonalization in Training DNNs☆25Updated 4 years ago
- ☆21Updated 5 years ago
- Official PyTorch code for CVPR 2021 paper "AutoDO: Robust AutoAugment for Biased Data with Label Noise via Scalable Probabilistic Implici…☆24Updated 3 years ago