kenya-sk / mc_dropout_tensorflowLinks
This repository reimplemented "MC Dropout" by tensorflow 2.0 Eager Extension.
☆18Updated 2 years ago
Alternatives and similar repositories for mc_dropout_tensorflow
Users that are interested in mc_dropout_tensorflow are comparing it to the libraries listed below
Sorting:
- Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)☆137Updated 5 years ago
- Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments☆69Updated 5 years ago
- Code for "Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference" (NeurIPS Bayesian Deep Learning W…☆24Updated 5 years ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 2 years ago
- Implementation of the MNIST experiment for Monte Carlo Dropout from http://mlg.eng.cam.ac.uk/yarin/PDFs/NIPS_2015_bayesian_convnets.pdf☆30Updated 5 years ago
- ☆238Updated 5 years ago
- Code associated with ACM-CHIL 21 paper 'T-DPSOM - An Interpretable Clustering Method for Unsupervised Learning of Patient Health States'☆69Updated 4 years ago
- An encoder-decoder framework for learning from incomplete data☆45Updated last year
- Dropout as Regularization and Bayesian Approximation☆58Updated 6 years ago
- Code for the paper "Improving Missing Data Imputation with Deep Generative Models"☆32Updated 6 years ago
- Bayesian LSTM (Tensorflow)☆55Updated 2 years ago
- Implementation and evaluation of different approaches to get uncertainty in neural networks☆140Updated 7 years ago
- Uncertainty Estimation Using Deep Neural Network and Gradient Boosting Methods☆22Updated 4 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆56Updated 6 years ago
- inspired by 'Recurrent Neural Networks for Multivariate Time Series with Missing Values' pytorch ver☆117Updated 6 years ago
- ☆24Updated 6 years ago
- My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"☆138Updated 7 years ago
- Keras Implementation of adverserial autoencoder (AAE)☆56Updated 6 years ago
- A toy example of VAE-regression network☆72Updated 5 years ago
- conditional variational autoencoder written in Keras [not actively maintained]☆96Updated 7 years ago
- Replication of the paper "Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference" - Yarin Gal, Zoubin Gh…☆10Updated 7 years ago
- Implementation of the MIWAE method for deep generative modelling of incomplete data sets.☆41Updated last year
- Utilities to perform Uncertainty Quantification on Keras Models☆116Updated last year
- Demonstration code for missing data imputation using Variational Autoencoders (VAE)☆23Updated 6 years ago
- Pytorch implementations of various types of autoencoders☆66Updated 6 years ago
- Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates☆115Updated 4 years ago
- Sequence-to-sequence autoencoder for unsupervised learning of nonlinear dynamics (Tensorflow).☆30Updated 3 years ago
- Multi-Channel Variational Auto Encoder: A Bayesian Deep Learning Framework for Modeling High-Dimensional Heterogeneous Data.☆33Updated 4 years ago
- pytorch implementation of "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks" LSTM(https://arxiv.org/abs/1512.…☆21Updated 4 years ago
- ☆108Updated 3 years ago