mabirck / adaptative-dropout-pytorchLinks
Pytorch implementation of Adaptative Dropout a.ka Standout.
☆12Updated 7 years ago
Alternatives and similar repositories for adaptative-dropout-pytorch
Users that are interested in adaptative-dropout-pytorch are comparing it to the libraries listed below
Sorting:
- Code for our paper: "Regularity Normalization: Neuroscience-Inspired Unsupervised Attention across Neural Network Layers".☆21Updated 3 years ago
- Repository with code for paper "Inhibited Softmax for Uncertainty Estimation in Neural Networks"☆25Updated 6 years ago
- PyTorch implementation of "Improved Training of Wasserstein GANs", arxiv:1704.00028☆27Updated 7 years ago
- Implementation of Information Dropout☆39Updated 8 years ago
- [NeurIPS'19] [PyTorch] Adaptive Regularization in NN☆68Updated 5 years ago
- Uncertainty Autoencoders, AISTATS 2019☆55Updated 6 years ago
- ☆25Updated 2 years ago
- In this paper, we show that the performance of a learnt generative model is closely related to the model's ability to accurately represen…☆41Updated 4 years ago
- Applied Sparse regularization (L1), Weight decay regularization (L2), ElasticNet, GroupLasso and GroupSparseLasso to Neuronal Network.☆38Updated 3 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Code for ICLR2018 paper: Improving GAN Training via Binarized Representation Entropy (BRE) Regularization - Y. Cao · W Ding · Y.C. Lui · …☆20Updated 7 years ago
- A pytorch implementation of Information Bottleneck GAN☆28Updated 6 years ago
- Domain Agnostic Normalization layer for Unsupervised Domain Adaptation☆11Updated 2 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆112Updated 6 years ago
- Implementation of the Sliced Wasserstein Autoencoders☆91Updated 7 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- ☆34Updated 6 years ago
- Uncertainty interpretations of the neural network☆32Updated 7 years ago
- model uncertainty using mc dropout☆20Updated 6 years ago
- Lifelong Variational Autoencoder☆14Updated 7 years ago
- A clean TensorFlow implementation of Concrete Dropout☆22Updated 7 years ago
- Implementation of Visual Feature Attribution using Wasserstein GANs (VAGANs, https://arxiv.org/abs/1711.08998) in PyTorch☆93Updated 2 years ago
- Pytorch Adversarial Auto Encoder (AAE)☆87Updated 6 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆53Updated 6 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆49Updated 7 years ago
- ☆53Updated 7 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 6 years ago
- Code for "Bridging the Gap between f-GANs and Wasserstein GANs", ICML 2020☆14Updated 5 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆35Updated 5 years ago
- Pytorch implementation of contractive autoencoder on MNIST dataset☆53Updated 7 years ago