51 citations · 116 across the 15 of their papers we have counts for
3 papers · 1 filter
Neural Belief Propagation for Scene Graph Generation
Daqi Liu, Miroslaw Bober, Josef Kittler
Scene graph generation aims to interpret an input image by explicitly modelling the potential objects and their relationships, which is predominantly solved by the message passing…
Learning PAC-Bayes Priors for Probabilistic Neural Networks
Maria Perez-Ortiz, Omar Rivasplata, Benjamin Guedj +5
Recent works have investigated deep learning models trained by optimising PAC-Bayes bounds, with priors that are learnt on subsets of the data. This combination has been shown to l…
Understanding the Distributions of Aggregation Layers in Deep Neural Networks
Eng-Jon Ong, Sameed Husain, Miroslaw Bober
The process of aggregation is ubiquitous in almost all deep nets models. It functions as an important mechanism for consolidating deep features into a more compact representation,…