Dr Angelica Aviles Rivero | Department of Pure Mathematics and Mathematical Statistics

skip to content

➡️ 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: $\bigstar$ Applied 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)

(link to publication)

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)

(doi: 10.48550/arxiv.2211.06885)

(link to publication)

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)

(link to publication)

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)

(link to publication)

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 : a publication of the IEEE Signal Processing Society

(2022)

31,

1805

(doi: 10.1109/tip.2022.3144036)

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

(doi: 10.1148/radiol.2021210391)

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 recognition

(2021)

122,

108274

(doi: 10.1016/j.patcog.2021.108274)

Learning optical flow for fast MRI reconstruction

T Schmoderer, AI Aviles-Rivero, V Corona, N Debroux, CB Schönlieb

– Inverse Problems

(2021)

37,

095007

(doi: 10.1088/1361-6420/ac164a)

Delving Into Deep Walkers: A Convergence Analysis of Random-Walk-Based Vertex Embeddings

D Kloepfer, AI Aviles-Rivero, D Heydecker

(2021)

(link to publication)

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)

(link to publication)