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GitHub topics: monte-carlo-dropout

harrisonpim/uncertainty

🤔 Methods for measuring and visualising the uncertainty in neural networks

Language: Jupyter Notebook - Size: 168 KB - Last synced: about 2 months ago - Pushed: about 2 months ago - Stars: 0 - Forks: 0

FedericoVasile1/bayesian-cnn

Comparison of a network implemented via Variational Inference with the same network implemented via Monte Carlo Dropout

Language: Jupyter Notebook - Size: 49.3 MB - Last synced: about 1 month ago - Pushed: about 3 years ago - Stars: 2 - Forks: 1

JortdeJong13/epistemic-uncertainty

Epistemic uncertainty, sometimes referred to as model uncertainty, describes what the model does not know because training data was not appropriate. Modelling epistemic uncertainty is crucial to prevent ill advised discussion making due to over confident models.

Language: Jupyter Notebook - Size: 8.74 MB - Last synced: 4 months ago - Pushed: 7 months ago - Stars: 0 - Forks: 0

negarhdr/FER_PSTBLN_MCD

PyTorch implementation of landmark-based facial expression recognition using Spatio-Temporal BiLinear Networks (ST-BLN)

Language: Python - Size: 106 KB - Last synced: 8 months ago - Pushed: almost 2 years ago - Stars: 4 - Forks: 1

akashmondal1810/UncertaintyEstimation

Uncertainty Estimation Using Deep Neural Network and Gradient Boosting Methods

Language: Python - Size: 9.29 MB - Last synced: 12 months ago - Pushed: almost 3 years ago - Stars: 15 - Forks: 5

ronaldseoh/bayesian-dl-experiments

Bayesian deep learning experiments

Language: Jupyter Notebook - Size: 171 MB - Last synced: about 1 year ago - Pushed: almost 4 years ago - Stars: 8 - Forks: 2

sungyubkim/MCDO

A pytorch implementation of MCDO(Monte-Carlo Dropout methods)

Language: Jupyter Notebook - Size: 233 KB - Last synced: about 1 year ago - Pushed: over 5 years ago - Stars: 37 - Forks: 7

kenneym/bug_classification_research

An NLP Model used for automated assignment of bug reports to the relevant engineering team. Utilizes a novel confidence bounding approach - Monte Carlo Dropout, and assigns underconfident predictions to a queue for human review. Built for Pegasystems Inc.

Language: Jupyter Notebook - Size: 41.1 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 4 - Forks: 1

ronaldseoh/ronald_bdl

An experimental Python package for learning Bayesian Neural Network.

Language: Python - Size: 60.5 KB - Last synced: about 1 year ago - Pushed: almost 4 years ago - Stars: 6 - Forks: 1

lpcinelli/probabilistic-nn

Probabilistic approach to neural nets - modern scalable approximate inference methods

Language: Jupyter Notebook - Size: 397 KB - Last synced: about 1 year ago - Pushed: over 4 years ago - Stars: 1 - Forks: 0

ronaldseoh/DropoutUncertaintyExps Fork of yaringal/DropoutUncertaintyExps

(Forked Version) Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"

Language: Jupyter Notebook - Size: 5.11 MB - Last synced: about 1 year ago - Pushed: about 4 years ago - Stars: 2 - Forks: 2

GilbertoCunha/LHC-VLQ-Classifier

A Deep Learning Neural Network that classifies Vector Like Quarks from background events using generated collider data

Language: Jupyter Notebook - Size: 9.18 MB - Last synced: about 1 year ago - Pushed: over 3 years ago - Stars: 0 - Forks: 0

Related Keywords
monte-carlo-dropout 12 bayesian-deep-learning 6 variational-inference 5 deep-learning 4 pytorch 4 dropout 3 machine-learning 3 bayesian-neural-network 3 bayesian-neural-networks 3 vi 2 reproducibility 2 pyro 2 mc-dropout 2 convolutional-neural-networks 2 bayesian-inference 2 jupyter-notebook 2 uncertainty-estimation 2 hmc 2 mcmc 1 uncertainty-neural-networks 1 experiments 1 variational-dropout 1 mlops 1 nlp 1 rest-api 1 tensorflow 1 hamiltonian-monte-carlo 1 approximate-inference 1 expectation-propagation 1 keras 1 deep-neural-networks 1 particle-physics 1 quarks 1 laplace-approximation 1 matplotlib 1 mnist 1 neural-network 1 bayes 1 bayes-by-backprop 1 image-recognition 1 model-confidence 1 out-of-distribution-detection 1 polyp-segmentation 1 segmentation 1 uncertainty 1 variational-autoencoder 1 facial-expression-recognition 1 graph-convolutional-networks 1 deep-ensemble 1 predictive-uncertainty 1 probabilistic-models 1 xgboost 1 bayesian-dl-experiments 1 convolutional-neural-network 1