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Department of Pure Mathematics and Mathematical Statistics

 

➡️ Personal Home Page

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

NorMatch: Matching Normalizing Flows with Discriminative Classifiers for Semi-Supervised Learning
Z Deng, R Ke, C-B Schonlieb, AI Aviles-Rivero
(2022)
SCOTCH and SODA: A Transformer Video Shadow Detection Framework
L Liu, J Prost, L Zhu, N Papadakis, P Liò, C-B Schönlieb, AI Aviles-Rivero
(2022)
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,
210391
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)
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Room

F0.08a

Telephone

01223 760377