7 citations · 17 across the 21 of their papers we have counts for
5 papers · 1 filter
Improving Robot Localisation by Ignoring Visual Distraction
Oscar Mendez, Matthew Vowels, Richard Bowden
Attention is an important component of modern deep learning. However, less emphasis has been put on its inverse: ignoring distraction. Our daily lives require us to explicitly avoi…
BERT meets LIWC: Exploring State-of-the-Art Language Models for Predicting Communication Behavior in Couples' Conflict Interactions
Jacopo Biggiogera, George Boateng, Peter Hilpert +5
Many processes in psychology are complex, such as dyadic interactions between two interacting partners (e.g. patient-therapist, intimate relationship partners). Nevertheless, many…
Shadow-Mapping for Unsupervised Neural Causal Discovery
Matthew J. Vowels, Necati Cihan Camgoz, Richard Bowden
An important goal across most scientific fields is the discovery of causal structures underling a set of observations. Unfortunately, causal discovery methods which are based on co…
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery
Matthew J. Vowels, Necati Cihan Camgoz, Richard Bowden
Causal reasoning is a crucial part of science and human intelligence. In order to discover causal relationships from data, we need structure discovery methods. We provide a review…
VDSM: Unsupervised Video Disentanglement with State-Space Modeling and Deep Mixtures of Experts
Matthew J. Vowels, Necati Cihan Camgoz, Richard Bowden
Disentangled representations support a range of downstream tasks including causal reasoning, generative modeling, and fair machine learning. Unfortunately, disentanglement has been…