Xiao Liu

Orcid: 0000-0003-1270-6302

Affiliations:
  • University of Edinburgh, School of Engineering, UK
  • Canon Medical Research Europe Ltd., Edinburgh, UK


According to our database1, Xiao Liu authored at least 18 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Compositionally Equivariant Representation Learning.
IEEE Trans. Medical Imaging, June, 2024

2023
Group Distributionally Robust Knowledge Distillation.
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023

Compositional Representation Learning for Brain Tumour Segmentation.
Proceedings of the Domain Adaptation and Representation Transfer - 5th MICCAI Workshop, 2023

Diffusion Models for Causal Discovery via Topological Ordering.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Learning disentangled representations in the imaging domain.
Medical Image Anal., 2022

Why Patient Data Cannot Be Easily Forgotten?
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

What is Healthy? Generative Counterfactual Diffusion for Lesion Localization.
Proceedings of the Deep Generative Models - Second MICCAI Workshop, 2022

HSIC-InfoGAN: Learning Unsupervised Disentangled Representations by Maximising Approximated Mutual Information.
Proceedings of the Medical Applications with Disentanglements - First MICCAI Workshop, 2022

vMFNet: Compositionality Meets Domain-Generalised Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Applying Disentanglement in the Medical Domain: An Introduction for the MAD Workshop.
Proceedings of the Medical Applications with Disentanglements - First MICCAI Workshop, 2022

2021
Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge.
IEEE Trans. Medical Imaging, 2021

A Tutorial on Learning Disentangled Representations in the Imaging Domain.
CoRR, 2021

Controllable Cardiac Synthesis via Disentangled Anatomy Arithmetic.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Semi-supervised Meta-learning with Disentanglement for Domain-Generalised Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Measuring the Biases and Effectiveness of Content-Style Disentanglement.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020
Metrics for Exposing the Biases of Content-Style Disentanglement.
CoRR, 2020

Disentangled Representations for Domain-Generalized Cardiac Segmentation.
Proceedings of the Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges, 2020

Have You Forgotten? A Method to Assess if Machine Learning Models Have Forgotten Data.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020


  Loading...