Graph Based Spatial Position Mapping of Low-Grade Gliomas. - Sarah Parisot; Hugues Duffau; Stéphane Chemouny; Nikos Paragios (MICCAI (2), 2011)

Graph-based detection, segmentation & characterization of brain tumors. - Sarah Parisot; Hugues Duffau; Stéphane Chemouny; Nikos Paragios (CVPR, 2012)

Joint Tumor Segmentation and Dense Deformable Registration of Brain MR Images. - Sarah Parisot; Hugues Duffau; Stéphane Chemouny; Nikos Paragios (MICCAI (2), 2012)

Uncertainty-Driven Efficiently-Sampled Sparse Graphical Models for Concurrent Tumor Segmentation and Atlas Registration. - Sarah Parisot; William M. Wells III; Stéphane Chemouny; Hugues Duffau; Nikos Paragios (ICCV, 2013)

Concurrent tumor segmentation and registration with uncertainty-based sparse non-uniform graphs. - Sarah Parisot; William M. Wells III; Stéphane Chemouny; Hugues Duffau; Nikos Paragios (Medical Image Anal., 2014)

Joint Spectral Decomposition for the Parcellation of the Human Cerebral Cortex Using Resting-State fMRI. - Salim Arslan; Sarah Parisot; Daniel Rueckert (IPMI, 2015)

Tractography-Driven Groupwise Multi-scale Parcellation of the Cortex. - Sarah Parisot; Salim Arslan; Jonathan Passerat-Palmbach; William M. Wells III; Daniel Rueckert (IPMI, 2015)

Beyond the AHA 17-Segment Model: Motion-Driven Parcellation of the Left Ventricle. - Wenjia Bai; Devis Peressutti; Sarah Parisot; Ozan Oktay; Martin Rajchl; Declan P. O'Regan; Stuart A. Cook; Andrew P. King; Daniel Rueckert (STACOM@MICCAI, 2015)

A Continuous Flow-Maximisation Approach to Connectivity-Driven Cortical Parcellation. - Sarah Parisot; Martin Rajchl; Jonathan Passerat-Palmbach; Daniel Rueckert (MICCAI (3), 2015)

Boundary Mapping Through Manifold Learning for Connectivity-Based Cortical Parcellation. - Salim Arslan; Sarah Parisot; Daniel Rueckert (MICCAI (1), 2016)

DeepMedic for Brain Tumor Segmentation. - Konstantinos Kamnitsas; Enzo Ferrante; Sarah Parisot; Christian Ledig; Aditya V. Nori; Antonio Criminisi; Daniel Rueckert; Ben Glocker (BrainLes@MICCAI, 2016)

GraMPa: Graph-Based Multi-modal Parcellation of the Cortex Using Fusion Moves. - Sarah Parisot; Ben Glocker; Markus Schirmer; Daniel Rueckert (MICCAI (1), 2016)

Comparison of Brain Networks with Unknown Correspondences. - Sofia Ira Ktena; Sarah Parisot; Jonathan Passerat-Palmbach; Daniel Rueckert (CoRR, 2016)

Proceedings of the Workshop on Brain Analysis using COnnectivity Networks - BACON 2016. - Sarah Parisot; Jonathan Passerat-Palmbach; Markus D. Schirmer; Boris Gutman (CoRR, 2016)

(Hyper)-graphical models in biomedical image analysis. - Nikos Paragios; Enzo Ferrante; Ben Glocker; Nikos Komodakis; Sarah Parisot; Evangelia I. Zacharaki (Medical Image Anal., 2016)

Group-wise parcellation of the cortex through multi-scale spectral clustering. - Sarah Parisot; Salim Arslan; Jonathan Passerat-Palmbach; William M. Wells III; Daniel Rueckert (NeuroImage, 2016)

Exploring heritability of functional brain networks with inexact graph matching. - Sofia Ira Ktena; Salim Arslan; Sarah Parisot; Daniel Rueckert (ISBI, 2017)

Distance Metric Learning Using Graph Convolutional Networks: Application to Functional Brain Networks. - Sofia Ira Ktena; Sarah Parisot; Enzo Ferrante; Martin Rajchl; Matthew C. H. Lee; Ben Glocker; Daniel Rueckert (MICCAI (1), 2017)

Spectral Graph Convolutions for Population-Based Disease Prediction. - Sarah Parisot; Sofia Ira Ktena; Enzo Ferrante; Matthew C. H. Lee; Ricardo Guerrero Moreno; Ben Glocker; Daniel Rueckert (MICCAI (3), 2017)

Reproducible Large-Scale Neuroimaging Studies with the OpenMOLE Workflow Management System. - Jonathan Passerat-Palmbach; Romain Reuillon; Mathieu Leclaire; Antonios Makropoulos; Emma C. Robinson; Sarah Parisot; Daniel Rueckert (Frontiers Neuroinformatics, 2017)

A flexible graphical model for multi-modal parcellation of the cortex. - Sarah Parisot; Ben Glocker; Sofia Ira Ktena; Salim Arslan; Markus D. Schirmer; Daniel Rueckert (NeuroImage, 2017)

Uncertainty Quantification in CNN-Based Surface Prediction Using Shape Priors. - Katarína Tóthová; Sarah Parisot; Matthew C. H. Lee; Esther Puyol-Antón; Lisa M. Koch; Andrew P. King; Ender Konukoglu; Marc Pollefeys (ShapeMI@MICCAI, 2018)

Learning Conditioned Graph Structures for Interpretable Visual Question Answering. - Will Norcliffe-Brown; Stathis Vafeias; Sarah Parisot (NeurIPS, 2018)

Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer's Disease. - Sarah Parisot; Sofia Ira Ktena; Enzo Ferrante; Matthew Lee 010; Ricardo Guerrero; Ben Glocker; Daniel Rueckert (CoRR, 2018)

Meta-Learning for Few-shot Camera-Adaptive Color Constancy. - Steven McDonagh 001; Sarah Parisot; Zhenguo Li; Gregory G. Slabaugh (CoRR, 2018)

Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer's disease. - Sarah Parisot; Sofia Ira Ktena; Enzo Ferrante; Matthew C. H. Lee; Ricardo Guerrero; Ben Glocker; Daniel Rueckert (Medical Image Anal., 2018)

Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex. - Salim Arslan; Sofia Ira Ktena; Antonios Makropoulos; Emma C. Robinson; Daniel Rueckert; Sarah Parisot (NeuroImage, 2018)

Metric learning with spectral graph convolutions on brain connectivity networks. - Sofia Ira Ktena; Sarah Parisot; Enzo Ferrante; Martin Rajchl; Matthew C. H. Lee; Ben Glocker; Daniel Rueckert (NeuroImage, 2018)

Continual learning: A comparative study on how to defy forgetting in classification tasks. - Matthias De Lange; Rahaf Aljundi; Marc Masana; Sarah Parisot; Xu Jia 012; Ales Leonardis; Gregory G. Slabaugh; Tinne Tuytelaars (CoRR, 2019)

EHSOD: CAM-Guided End-to-End Hybrid-Supervised Object Detection with Cascade Refinement. - Linpu Fang; Hang Xu 004; Zhili Liu; Sarah Parisot; Zhenguo Li (AAAI, 2020)

A Multi-Hypothesis Approach to Color Constancy. - Daniel Hernández Juárez; Sarah Parisot; Benjamin Busam; Ales Leonardis; Gregory G. Slabaugh; Steven McDonagh 001 (CVPR, 2020)

Unsupervised Model Personalization While Preserving Privacy and Scalability: An Open Problem. - Matthias De Lange; Xu Jia 012; Sarah Parisot; Ales Leonardis; Gregory G. Slabaugh; Tinne Tuytelaars (CVPR, 2020)

DeepLPF: Deep Local Parametric Filters for Image Enhancement. - Sean Moran; Pierre Marza; Steven McDonagh 001; Sarah Parisot; Gregory G. Slabaugh (CVPR, 2020)

More Classifiers, Less Forgetting: A Generic Multi-classifier Paradigm for Incremental Learning. - Yu Liu 012; Sarah Parisot; Gregory G. Slabaugh; Xu Jia 012; Ales Leonardis; Tinne Tuytelaars (ECCV (26), 2020)

Many-Shot from Low-Shot: Learning to Annotate Using Mixed Supervision for Object Detection. - Carlo Biffi; Steven McDonagh 001; Philip H. S. Torr; Ales Leonardis; Sarah Parisot (ECCV (8), 2020)

Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors. - Mateusz Michalkiewicz; Sarah Parisot; Stavros Tsogkas; Mahsa Baktashmotlagh; Anders P. Eriksson; Eugene Belilovsky (ECCV (25), 2020)

Low Light Video Enhancement Using Synthetic Data Produced with an Intermediate Domain Mapping. - Danai Triantafyllidou; Sean Moran; Steven McDonagh 001; Sarah Parisot; Gregory G. Slabaugh (ECCV (13), 2020)

Probabilistic 3D Surface Reconstruction from Sparse MRI Information. - Katarína Tóthová; Sarah Parisot; Matthew C. H. Lee; Esther Puyol-Antón; Andrew P. King; Marc Pollefeys; Ender Konukoglu (MICCAI (1), 2020)

Learning Compositional Shape Priors for Few-Shot 3D Reconstruction. - Mateusz Michalkiewicz; Stavros Tsogkas; Sarah Parisot; Mahsa Baktashmotlagh; Anders P. Eriksson; Eugene Belilovsky (CoRR, 2021)

Content-Diverse Comparisons improve IQA. - William Thong; José Costa Pereira; Sarah Parisot; Ales Leonardis; Steven McDonagh 001 (BMVC, 2022)

Re-examining Distillation for Continual Object Detection. - Eli Verwimp; Kuo Yang; Sarah Parisot; Lanqing Hong; Steven McDonagh 001; Eduardo Pérez-Pellitero; Matthias De Lange; Tinne Tuytelaars (BMVC, 2022)

Long-tail Recognition via Compositional Knowledge Transfer. - Sarah Parisot; Pedro M. Esperança; Steven McDonagh 001; Tamas J. Madarasz; Yongxin Yang; Zhenguo Li (CVPR, 2022)

A Continual Learning Survey: Defying Forgetting in Classification Tasks. - Matthias De Lange; Rahaf Aljundi; Marc Masana; Sarah Parisot; Xu Jia 012; Ales Leonardis; Gregory G. Slabaugh; Tinne Tuytelaars (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Learning to Name Classes for Vision and Language Models. - Sarah Parisot; Yongxin Yang; Steven McDonagh 001 (CVPR, 2023)

Optimisation-Based Multi-Modal Semantic Image Editing. - Bowen Li; Yongxin Yang; Steven McDonagh 001; Shifeng Zhang; Petru-Daniel Tudosiu; Sarah Parisot (CoRR, 2023)

CLAD: A realistic Continual Learning benchmark for Autonomous Driving. - Eli Verwimp; Kuo Yang; Sarah Parisot; Lanqing Hong; Steven McDonagh 001; Eduardo Pérez-Pellitero; Matthias De Lange; Tinne Tuytelaars (Neural Networks, 2023)

Improving Object Detection via Local-global Contrastive Learning. - Danai Triantafyllidou; Sarah Parisot; Ales Leonardis; Steven McDonagh 001 (BMVC, 2024)

MULAN: A Multi Layer Annotated Dataset for Controllable Text-to-Image Generation. - Petru-Daniel Tudosiu; Yongxin Yang; Shifeng Zhang; Fei Chen; Steven McDonagh 001; Gerasimos Lampouras; Ignacio Iacobacci; Sarah Parisot (CVPR, 2024)

Generating compositional scenes via Text-to-image RGBA Instance Generation. - Alessandro Fontanella; Petru-Daniel Tudosiu; Yongxin Yang; Shifeng Zhang; Sarah Parisot (NeurIPS, 2024)

Exploiting Mixture-of-Experts Redundancy Unlocks Multimodal Generative Abilities. - Raman Dutt; Harleen Hanspal; Guoxuan Xia; Petru-Daniel Tudosiu; Alexander Black 001; Yongxin Yang; Steven McDonagh 001; Sarah Parisot (CoRR, 2025)

Adapting Vision-Language Models for Evaluating World Models. - Mariya Hendriksen; Tabish Rashid; David Bignell; Raluca Georgescu; Abdelhak Lemkhenter; Katja Hofmann; Sam Devlin; Sarah Parisot (CoRR, 2025)

A Practical Investigation of Spatially-Controlled Image Generation with Transformers. - Guoxuan Xia; Harleen Hanspal; Petru-Daniel Tudosiu; Shifeng Zhang; Sarah Parisot (CoRR, 2025)