10 citations · 12 across the 3 of their papers we have counts for
4 papers
Adversarial learning of cancer tissue representations
Adalberto Claudio Quiros, Nicolas Coudray, Anna Yeaton +4
Deep learning based analysis of histopathology images shows promise in advancing the understanding of tumor progression, tumor micro-environment, and their underpinning biological…
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.…
Tomographic Auto-Encoder: Unsupervised Bayesian Recovery of Corrupted Data
Francesco Tonolini, Pablo G. Moreno, Andreas Damianou +1
We propose a new probabilistic method for unsupervised recovery of corrupted data. Given a large ensemble of degraded samples, our method recovers accurate posteriors of clean valu…
Variational Inference for Computational Imaging Inverse Problems
Francesco Tonolini, Jack Radford, Alex Turpin +2
Machine learning methods for computational imaging require uncertainty estimation to be reliable in real settings. While Bayesian models offer a computationally tractable way of re…