probabilistic-deep-learning

Here are 6 public repositories matching this topic...

mohd-faizy / Probabilistic-Deep-Learning-with-TensorFlow

Probabilistic Deep Learning finds its application in autonomous vehicles and medical diagnoses. This is an increasingly important area of deep learning that aims to quantify the noise and uncertainty that is often present in real-world datasets.

machine-learning tensorflow keras multivariate-distributions probabilistic-programming poisson-distribution univariate-distributions bernoulli-distribution tfp tensorflow-probability tensorflow2 binomial-distributions probabilistic-deep-learning deep-probabilistic-models probabilistic-layers

Updated Apr 15, 2023
Jupyter Notebook

IntelLabs / AVUC

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Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.

deep-learning uncertainty-neural-networks model-calibration uncertainty-quantification uncertainty-estimation variational-inference bayesian-deep-learning probabilistic-neural-network probabilistic-deep-learning uncertainty-calibration

Updated Dec 16, 2022
Python

prs-eth / FILM-Ensemble

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[NeurIPS 2022] FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear Modulation

deep-learning pytorch calibration ensemble ece cifar10 cifar100 neurips probabilistic-deep-learning sub-models uncertanity feature-wise-linear-modulation implicit-ensemble

Updated Dec 19, 2022
Python

itsayushthada / Probabislitc-Deep-Learning

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Exploration of TensorFlow-2 and TensorFlow probability to implement Bayesian Neural Networks, Normalizing flows, real NVPs and Autoencoders. Exploration of Bayesian Modelling and Variational Inference with Pyro.

deep-learning bayesian-inference variational-inference bayesian-machine-learning pyro bayesian-neural-networks tensorflow-probability tensorflow-2 probabilistic-deep-learning probabilistic-modelling