139 citations · 787 across the 16 of their papers we have counts for
6 papers · 1 filter
Rasa: Open Source Language Understanding and Dialogue Management
Tom Bocklisch, Joey Faulkner, Nick Pawlowski +1
We introduce a pair of tools, Rasa NLU and Rasa Core, which are open source python libraries for building conversational software. Their purpose is to make machine-learning based d…
DLTK: State of the Art Reference Implementations for Deep Learning on Medical Images
Nick Pawlowski, Sofia Ira Ktena, Matthew C. H. Lee +4
We present DLTK, a toolkit providing baseline implementations for efficient experimentation with deep learning methods on biomedical images. It builds on top of TensorFlow and its…
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation
Konstantinos Kamnitsas, Wenjia Bai, Enzo Ferrante +8
Deep learning approaches such as convolutional neural nets have consistently outperformed previous methods on challenging tasks such as dense, semantic segmentation. However, the v…
Implicit Weight Uncertainty in Neural Networks
Nick Pawlowski, Andrew Brock, Matthew C. H. Lee +2
Modern neural networks tend to be overconfident on unseen, noisy or incorrectly labelled data and do not produce meaningful uncertainty measures. Bayesian deep learning aims to add…
Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning
Nat Dilokthanakul, Christos Kaplanis, Nick Pawlowski +1
The problem of sparse rewards is one of the hardest challenges in contemporary reinforcement learning. Hierarchical reinforcement learning (HRL) tackles this problem by using a set…
Efficient variational Bayesian neural network ensembles for outlier detection
Nick Pawlowski, Miguel Jaques, Ben Glocker
In this work we perform outlier detection using ensembles of neural networks obtained by variational approximation of the posterior in a Bayesian neural network setting. The variat…