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:
- Repository with code for paper "Inhibited Softmax for Uncertainty Estimation in Neural Networks"☆25Updated 6 years ago
- [NeurIPS'19] [PyTorch] Adaptive Regularization in NN☆68Updated 5 years ago
- Uncertainty Autoencoders, AISTATS 2019☆55Updated 6 years ago
- Implementation of Information Dropout☆39Updated 8 years ago
- Code for our paper: "Regularity Normalization: Neuroscience-Inspired Unsupervised Attention across Neural Network Layers".☆21Updated 3 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆49Updated 7 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Official PyTorch implementation of the paper : ProbAct: A Probabilistic Activation Function for Deep Neural Networks.☆13Updated 6 years ago
- Lifelong Variational Autoencoder☆14Updated 7 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
- This repository contains the code used in a publication 'Active Learning for Decision-Making from Imbalanced Observational Data', Iiris S…☆11Updated 6 years ago
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 5 years ago
- ☆25Updated 3 years ago
- model uncertainty using mc dropout☆20Updated 6 years ago
- Uncertainty interpretations of the neural network☆32Updated 7 years ago
- Implementation of the LOSSGRAD optimization algorithm☆15Updated 6 years ago
- PyTorch implementation of "Improved Training of Wasserstein GANs", arxiv:1704.00028☆27Updated 7 years ago
- A pytorch implementation of Information Bottleneck GAN☆28Updated 6 years ago
- ☆53Updated 7 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆66Updated 5 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆35Updated 5 years ago
- This is the code for our paper: Semi-Supervised Learning With GANs: Revisiting Manifold Regularization (ICLR 2018)☆44Updated 6 years ago
- A clean TensorFlow implementation of Concrete Dropout☆22Updated 7 years ago
- The Variational Homoencoder: Learning to learn high capacity generative models from few examples☆34Updated 2 years ago
- Pytorch Adversarial Auto Encoder (AAE)☆87Updated 6 years ago
- LVAE: Ladder Variational Auto-Encoders (NIPS 2016) with TensorFlow.☆16Updated 7 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- Implementation of the Sliced Wasserstein Autoencoders☆90Updated 7 years ago
- ☆61Updated 2 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 6 years ago