Philip Sellars

University of Cambridge — United Kingdom

Medicine · Health Sciences

6h-index138citations15works0.02yr avg
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Research Topics

COVID-19 diagnosis using AI(5), Radiomics and Machine Learning in Medical Imaging(4), AI in cancer detection(3), Domain Adaptation and Few-Shot Learning(3), Machine Learning and Data Classification(3)

Publications15 total

LaplaceNet: A Hybrid Graph-Energy Neural Network for Deep Semisupervised Classification
IEEE Transactions on Neural Networks and Learning Systems·2022· 16 citedOpen Access
GraphXCOVID: Explainable deep graph diffusion pseudo-Labelling for identifying COVID-19 on chest X-rays
Pattern Recognition·2021· 6 citedOpen Access
LaplaceNet: A Hybrid Energy-Neural Model for Deep Semi-Supervised Classification
arXiv (Cornell University)·2021· 10 citedOpen Access
GraphXCOVID: Explainable Deep Graph Diffusion Pseudo-Labelling for\n Identifying COVID-19 on Chest X-rays
arXiv (Cornell University)·2020· 34 citedOpen Access
The GraphNet Zoo: An All-in-One Graph Based Deep Semi-Supervised\n Framework for Medical Image Classification
arXiv (Cornell University)·2020Open Access
The GraphNet Zoo: A Plug-and-Play Framework for Deep Semi-Supervised Classification.
2020
Two Cycle Learning: Clustering Based Regularisation for Deep Semi-Supervised Classification.
2020· 5 cited
CycleCluster: Modernising Clustering Regularisation for Deep Semi-Supervised Classification
arXiv (Cornell University)·2020Open Access
The GraphNet Zoo: An All-in-One Graph Based Deep Semi-supervised Framework for Medical Image Classification
Lecture notes in computer science·2020· 2 citedOpen Access
GraphX$^{NET}-$ Chest X-Ray Classification Under Extreme Minimal Supervision
arXiv (Cornell University)·2019· 13 citedOpen Access
GraphX$^{NET}-$ Chest X-Ray Classification Under Extreme Minimal\n Supervision
arXiv (Cornell University)·2019· 29 citedOpen Access
Semi-Supervised Learning with Graphs: Covariance Based Superpixels For Hyperspectral Image Classification
2019Open Access
Energy Models for Better Pseudo-Labels: Improving Semi-Supervised Classification with the 1-Laplacian Graph Energy
arXiv (Cornell University)·2019Open Access
GraphX$$^\mathbf{\small NET } -$$ Chest X-Ray Classification Under Extreme Minimal Supervision
Lecture notes in computer science·2019· 23 cited
Pre-LBA ISLSCP Initiative I Data
Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics·2012Open Access

Frequent Co-authors

Angelica I. Avilés-Rivero(14), Carola‐Bibiane Schönlieb(10), Nicolas Papadakis(7), Ruoteng Li(4), Qingnan Fan(3), Robby T. Tan(3), Marianne de Vriendt(3), David A. Coomes(1), Anita Faul(1), Carola-Bibane Schönlieb(1), Samar M. Alsaleh(1), Dengxin Dai(1)