alexrakowski / mc-dropout-mnistLinks
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
Alternatives and similar repositories for mc-dropout-mnist
Users that are interested in mc-dropout-mnist are comparing it to the libraries listed below
Sorting:
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 3 years ago
- Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)☆137Updated 6 years ago
- Implementation and evaluation of different approaches to get uncertainty in neural networks☆141Updated 7 years ago
- My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"☆139Updated 7 years ago
- Master Thesis on Bayesian Convolutional Neural Network using Variational Inference☆264Updated 6 years ago
- ☆239Updated 5 years ago
- Dropout as Regularization and Bayesian Approximation☆58Updated 6 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 5 years ago
- " Weight Uncertainty in Neural Networks"☆49Updated 7 years ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆176Updated 3 years ago
- Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments☆70Updated 5 years ago
- Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'☆61Updated 7 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆57Updated 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
- A tutorial for the 2018 paper Accurate Uncertainties for Deep Learning Using Calibrated Regression by Kuleshov et al.☆52Updated 5 years ago
- Learning error bars for neural network predictions☆71Updated 5 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆77Updated 2 years ago
- Gaussian Process Prior Variational Autoencoder☆86Updated 6 years ago
- TensorFlow Probability Tutorial☆37Updated 6 years ago
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆575Updated 3 years ago
- Utilities to perform Uncertainty Quantification on Keras Models☆119Updated last year
- ☆91Updated 2 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 7 years ago
- Bayesian Neural Network in PyTorch☆91Updated last year
- ☆25Updated 3 years ago
- Code associated with ACM-CHIL 21 paper 'T-DPSOM - An Interpretable Clustering Method for Unsupervised Learning of Patient Health States'☆70Updated 4 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆272Updated 3 years ago
- Replication of the paper "Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference" - Yarin Gal, Zoubin Gh…☆10Updated 7 years ago
- Reproducing the results of the paper "Bayesian Recurrent Neural Networks" by Fortunato et al.☆40Updated 7 years ago
- truncated Gaussian-Mixture Variational AutoEncoder☆11Updated 6 years ago