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Faculty of Mathematics

 

 

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My research lies  at the intersection of computational mathematics and machine learning for applications to large-scale real world problems. My central research is to develop new data-driven algorithmic techniques that allow computers to gain high-level understanding from vast amounts of data, this, with the aim of aiding the decisions of users. These methods are based on mathematical modelling and machine learning methods.

Keywords: \bigstarApplied Mathematics \bigstar Computational Mathematics \bigstar Inverse problems \bigstar  Image Analysis  \bigstar Graph Learning \bigstar Machine Learning.

 

Publications

LaplaceNet: A Hybrid Graph-Energy Neural Network for Deep Semisupervised Classification.
P Sellars, AI Aviles-Rivero, C-B Schonlieb
– IEEE transactions on neural networks and learning systems
(2022)
PP,
1
Why Deep Surgical Models Fail?: Revisiting Surgical Action Triplet Recognition through the Lens of Robustness
Y Cheng, L Liu, S Wang, Y Jin, C-B Schönlieb, AI Aviles-Rivero
(2022)
Multi-Modal Hypergraph Diffusion Network with Dual Prior for Alzheimer Classification
AI Aviles-Rivero, C Runkel, N Papadakis, Z Kourtzi, C-B Schönlieb
– MICCAI 2022
(2022)
A Three-Stage Self-Training Framework for Semi-Supervised Semantic Segmentation.
R Ke, AI Aviles-Rivero, S Pandey, S Reddy, C-B Schonlieb
– IEEE Transactions on Image Processing
(2022)
31,
1805
Machine Learning for Workflow Applications in Screening Mammography: Systematic Review and Meta-Analysis.
SE Hickman, R Woitek, EPV Le, YR Im, C Mouritsen Luxhøj, AI Aviles-Rivero, GC Baxter, JW MacKay, FJ Gilbert
– Radiology
(2021)
302,
88
GraphXCOVID: Explainable deep graph diffusion pseudo-Labelling for identifying COVID-19 on chest X-rays
AI Aviles-Rivero, P Sellars, C-B Schönlieb, N Papadakis
– Pattern Recognit
(2021)
122,
108274
Learning optical flow for fast MRI reconstruction
T Schmoderer, AI Aviles-Rivero, V Corona, N Debroux, CB Schönlieb
– Inverse Problems
(2021)
37,
095007
Delving Into Deep Walkers: A Convergence Analysis of Random-Walk-Based Vertex Embeddings
D Kloepfer, AI Aviles-Rivero, D Heydecker
(2021)
LaplaceNet: A Hybrid Graph-Energy Neural Network for Deep Semi-Supervised Classification
P Sellars, AI Aviles-Rivero, C-B Schönlieb
– IEEE Transactions on Neural Networks and Learning Systems 2022
(2021)
Dynamic spectral residual superpixels
J Zhang, AI Aviles-Rivero, D Heydecker, X Zhuang, R Chan, CB Schönlieb
– Pattern Recognition
(2021)
112,
107705
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Research Groups

Cambridge Image Analysis
Centre for Mathematical Imaging in Healthcare
Statistical Laboratory

Room

F0.08

Telephone

01223 760377