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:
- Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments☆70Updated 5 years ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 3 years ago
- Demonstration code for missing data imputation using Variational Autoencoders (VAE)☆23Updated 6 years ago
- Code for the paper "Improving Missing Data Imputation with Deep Generative Models"☆32Updated 6 years ago
- ☆239Updated 5 years ago
- conditional variational autoencoder written in Keras [not actively maintained]☆97Updated 8 years ago
- inspired by 'Recurrent Neural Networks for Multivariate Time Series with Missing Values' pytorch ver☆118Updated 6 years ago
- Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)☆137Updated 6 years ago
- TensorFlow implementation of the SOM-VAE model as described in https://arxiv.org/abs/1806.02199☆197Updated 2 years ago
- ☆43Updated 6 years ago
- Bayesian LSTM (Tensorflow)☆56Updated 2 years ago
- A toy example of VAE-regression network☆72Updated 5 years ago
- Semi-Supervised Learning with Ladder Networks in Keras. Get 98% test accuracy on MNIST with just 100 labeled examples !☆101Updated 4 years ago
- Dropout as Regularization and Bayesian Approximation☆58Updated 7 years ago
- Code associated with ACM-CHIL 21 paper 'T-DPSOM - An Interpretable Clustering Method for Unsupervised Learning of Patient Health States'☆72Updated 4 years ago
- Pytorch implementation of GRU-ODE-Bayes☆231Updated 3 years ago
- ICML paper 'High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach'☆92Updated 5 years ago
- Master Thesis on Bayesian Convolutional Neural Network using Variational Inference☆264Updated 6 years ago
- A deep clustering algorithm. Code to reproduce results for our paper N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of …☆137Updated 2 years ago
- This repository has implementation and tutorial for Deep Belief Network☆101Updated 7 years ago
- SSIM - A Deep Learning Approach for Recovering Missing Time Series Sensor Data☆40Updated 4 years ago
- Code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance☆77Updated 6 years ago
- Building a Bayesian deep learning classifier☆492Updated 8 years ago
- Uncertainty Estimation Using Deep Neural Network and Gradient Boosting Methods☆22Updated 4 years ago
- Pytorch implementations of various types of autoencoders☆65Updated 7 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
- PyTorch implementation of "MIDA: Multiple Imputation using Denoising Autoencoders"☆28Updated 6 years ago
- Code for "Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference" (NeurIPS Bayesian Deep Learning W…☆24Updated 5 years ago
- ☆84Updated 3 years ago
- Pytorch Deep Clustering with Convolutional Autoencoders implementation☆108Updated 5 years ago