VITA-Group / Orthogonality-in-CNNsLinks
[NeurIPS '18] "Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?" Official Implementation.
☆129Updated 3 years ago
Alternatives and similar repositories for Orthogonality-in-CNNs
Users that are interested in Orthogonality-in-CNNs are comparing it to the libraries listed below
Sorting:
- Implementation of the reversible residual network in pytorch☆105Updated 3 years ago
- This project is the Torch implementation of our accepted AAAI 2018 paper : orthogonal weight normalization method for solving orthogonali…☆57Updated 5 years ago
- Code for paper "Orthogonal Convolutional Neural Networks".☆118Updated 4 years ago
- Full implementation of the paper "Rethinking Softmax with Cross-Entropy: Neural Network Classifier as Mutual Information Estimator".☆102Updated 5 years ago
- This is the pytorch re-implementation of the IterNorm☆41Updated 6 years ago
- ☆66Updated 6 years ago
- Regularizing Meta-Learning via Gradient Dropout☆53Updated 5 years ago
- Deep Isometric Learning for Visual Recognition (ICML 2020)☆143Updated 3 years ago
- Improving MMD-GAN training with repulsive loss function☆89Updated 2 years ago
- [NeurIPS 2020 Oral] Is normalization indispensable for training deep neural networks?☆34Updated 3 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
- Code for the paper "Training CNNs with Selective Allocation of Channels" (ICML 2019)☆25Updated 6 years ago
- unsupervised video and image generation☆58Updated 5 years ago
- This repository contains code to replicate the experiments given in NeurIPS 2019 paper "One ticket to win them all: generalizing lottery …☆51Updated last year
- [ICLR 2019] ProbGAN: Towards Probabilistic GAN with Theoretical Guarantees☆32Updated 5 years ago
- Tensorflow implementation of S4L: Self-Supervised Semi-Supervised Learning☆94Updated 5 years ago
- ☆26Updated 6 years ago
- [ICML 2018] "Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions"☆152Updated 3 years ago
- [NeurIPS 2018] [JSAIT] PacGAN: The power of two samples in generative adversarial networks☆81Updated 4 years ago
- This project is the Torch implementation of our accepted CVPR 2019 paper, Iterative Normalization: Beyond Standardization towards Effic…☆25Updated 4 years ago
- PyTorch Implementation of CVPR'19 (oral) - Mitigating Information Leakage in Image Representations: A Maximum Entropy Approach☆28Updated 5 years ago
- Code for our paper "Informative Dropout for Robust Representation Learning: A Shape-bias Perspective" (ICML 2020)☆125Updated 2 years ago
- Lookahead: A Far-sighted Alternative of Magnitude-based Pruning (ICLR 2020)☆33Updated 4 years ago
- Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"☆119Updated 2 years ago
- ☆46Updated 2 years ago
- Implementation of soft parameter sharing for neural networks☆69Updated 4 years ago
- Sliced Wasserstein Generator☆39Updated 7 years ago
- Rethinking Feature Distribution for Loss Functions in Image Classification☆42Updated 2 years ago
- PyTorch and Torch implementation for our accepted CVPR 2020 paper (Oral): Controllable Orthogonalization in Training DNNs☆24Updated 4 years ago
- an implementation of L0 regularization with PyTorch☆57Updated 7 years ago