Semi-Supervised Learning with Graphs: Covariance Based Superpixels For Hyperspectral Image Classification. - Philip Sellars; Angelica I. Avilés-Rivero; Nicolas Papadakis; David Coomes; Anita Faul; Carola-Bibiane Schönlieb (IGARSS, 2019)

GraphX $$^ mathbf{ small NET } -$$ -Chest X-Ray Classification Under Extreme Minimal Supervision. - Angelica I. Avilés-Rivero; Nicolas Papadakis; Ruoteng Li; Philip Sellars; Qingnan Fan; Robby T. Tan; Carola-Bibiane Schönlieb (MICCAI (6), 2019)

GraphXNET-Chest X-Ray Classification Under Extreme Minimal Supervision. - Angelica I. Avilés-Rivero; Nicolas Papadakis; Ruoteng Li; Philip Sellars; Qingnan Fan; Robby T. Tan; Carola-Bibiane Schönlieb (CoRR, 2019)

The GraphNet Zoo: An All-in-One Graph Based Deep Semi-supervised Framework for Medical Image Classification. - Marianne de Vriendt; Philip Sellars; Angelica I. Avilés-Rivero (UNSURE/GRAIL@MICCAI, 2020)

Two Cycle Learning: Clustering Based Regularisation for Deep Semi-Supervised Classification. - Philip Sellars; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb (CoRR, 2020)

The GraphNet Zoo: A Plug-and-Play Framework for Deep Semi-Supervised Classification. - Marianne de Vriendt; Philip Sellars; Angelica I. Avilés-Rivero (CoRR, 2020)

Superpixel Contracted Graph-Based Learning for Hyperspectral Image Classification. - Philip Sellars; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb (IEEE Trans. Geosci. Remote. Sens., 2020)

LaplaceNet: A Hybrid Energy-Neural Model for Deep Semi-Supervised Classification. - Philip Sellars; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb (CoRR, 2021)

GraphXCOVID: Explainable deep graph diffusion pseudo-Labelling for identifying COVID-19 on chest X-rays. - Angelica I. Avilés-Rivero; Philip Sellars; Carola-Bibiane Schönlieb; Nicolas Papadakis (Pattern Recognit., 2022)

LaplaceNet: A Hybrid Graph-Energy Neural Network for Deep Semisupervised Classification. - Philip Sellars; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb (IEEE Trans. Neural Networks Learn. Syst., 2024)