10 citations · 16 across the 6 of their papers we have counts for
6 papers
Bessel Equivariant Networks for Inversion of Transmission Effects in Multi-Mode Optical Fibres
Joshua Mitton, Simon Peter Mekhail, Miles Padgett +3
We develop a new type of model for solving the task of inverting the transmission effects of multi-mode optical fibres through the construction of an -equivar…
Rotation Equivariant 3D Hand Mesh Generation from a Single RGB Image
Joshua Mitton, Chaitanya Kaul, Roderick Murray-Smith
We develop a rotation equivariant model for generating 3D hand meshes from 2D RGB images. This guarantees that as the input image of a hand is rotated the generated mesh undergoes…
CpT: Convolutional Point Transformer for 3D Point Cloud Processing
Chaitanya Kaul, Joshua Mitton, Hang Dai +1
We present CpT: Convolutional point Transformer - a novel deep learning architecture for dealing with the unstructured nature of 3D point cloud data. CpT is an improvement over exi…
Subgraph Permutation Equivariant Networks
Joshua Mitton, Roderick Murray-Smith
In this work we develop a new method, named Sub-graph Permutation Equivariant Networks (SPEN), which provides a framework for building graph neural networks that operate on sub-gra…
Rotation Equivariant Deforestation Segmentation and Driver Classification
Joshua Mitton, Roderick Murray-Smith
Deforestation has become a significant contributing factor to climate change and, due to this, both classifying the drivers and predicting segmentation maps of deforestation has at…
A Graph VAE and Graph Transformer Approach to Generating Molecular Graphs
Joshua Mitton, Hans M. Senn, Klaas Wynne +1
We propose a combination of a variational autoencoder and a transformer based model which fully utilises graph convolutional and graph pooling layers to operate directly on graphs.…