fabio-deep
Postdoc at Imperial College London | PhD in Computer Science
Imperial College LondonUnited Kingdom
fabio-deep's Stars
MilesCranmer/lagrangian_nns
Lagrangian Neural Networks
JavierAntoran/Bayesian-Neural-Networks
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
AntixK/PyTorch-VAE
A Collection of Variational Autoencoders (VAE) in PyTorch.
loretoparisi/CapsNet
CapsNet (Capsules Net) in Geoffrey E Hinton paper "Dynamic Routing Between Capsules" - State Of the Art
fcaliva/Binary_labelling_tool
fabio-deep/Variational-Capsule-Routing
Official Pytorch code for (AAAI 2020) paper "Capsule Routing via Variational Bayes", https://arxiv.org/pdf/1905.11455.pdf
ykwon0407/dagmm-1
A Pytorch implementation of the paper `Deep Autoencoding Gaussian Mixture Model For Unsupervised Anomaly Detection` by Zong et al.
ykwon0407/UQ_BNN
Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)
lsgos/uncertainty-adversarial-paper
Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'
yaringal/HeteroscedasticDropoutUncertainty
Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.
yaringal/ConcreteDropout
Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832
yaringal/multi-task-learning-example
A multi-task learning example for the paper https://arxiv.org/abs/1705.07115
yaringal/BayesianRNN
Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"