Loïc Le Folgoc

42 papers A* 3Journal 21Unranked 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Unsupervised Domain Adaptation with Target-Only Margin Disparity Discrepancy. CoRR Gauthier Miralles, Loïc Le Folgoc, Vincent Jugnon, Pietro Gori
2025	—	`conf`	Reducing Variability of Multiple Instance Learning Methods for Digital Pathology. MICCAI (7) Ali Mammadov, Loïc Le Folgoc, Guillaume Hocquet, Pietro Gori
2025	J	`jnl`	Reducing Variability of Multiple Instance Learning Methods for Digital Pathology. CoRR Ali Mammadov, Loïc Le Folgoc, Guillaume Hocquet, Pietro Gori
2025	J	`jnl`	Self-Supervision Enhances Instance-based Multiple Instance Learning Methods in Digital Pathology: A Benchmark Study. CoRR Ali Mammadov, Loïc Le Folgoc, Julien Adam, Anne Buronfosse, Gilles Hayem, Guillaume Hocquet, Pietro Gori
2024	—	`conf`	Dense Self-Supervised Learning for Medical Image Segmentation. MIDL Maxime Seince, Loïc Le Folgoc, Luiz Augusto Facury de Souza, Elsa D. Angelini
2024	J	`jnl`	Dense Self-Supervised Learning for Medical Image Segmentation. CoRR Maxime Seince, Loïc Le Folgoc, Luiz Augusto Facury de Souza, Elsa D. Angelini
2024	—	`conf`	Unsupervised Similarity Learning for Image Registration with Energy-Based Models. WBIR Daniel Grzech, Loïc Le Folgoc, Mohammad Farid Azampour, Athanasios Vlontzos, Ben Glocker, Nassir Navab, Julia A. Schnabel, Bernhard Kainz
2022	A*	`conf`	A variational Bayesian method for similarity learning in non-rigid image registration. CVPR Daniel Grzech, Mohammad Farid Azampour, Ben Glocker, Julia A. Schnabel, Nassir Navab, Bernhard Kainz, Loïc Le Folgoc
2021	J	`jnl`	Bayesian analysis of the prevalence bias: learning and predicting from imbalanced data. CoRR Loïc Le Folgoc, Vasileios Baltatzis, Amir Alansary, Sujal Desai, Anand Devaraj, Sam Ellis, Octavio E. Martinez Manzanera, Fahdi Kanavati, Arjun Nair, Julia A. Schnabel, Ben Glocker
2021	J	`jnl`	Is MC Dropout Bayesian? CoRR Loïc Le Folgoc, Vasileios Baltatzis, Sujal Desai, Anand Devaraj, Sam Ellis, Octavio E. Martinez Manzanera, Arjun Nair, Huaqi Qiu, Julia A. Schnabel, Ben Glocker
2021	—	`conf`	Patient-Specific 3d Cellular Automata Nodule Growth Synthesis In Lung Cancer Without The Need Of External Data. ISBI Octavio E. Martinez Manzanera, Sam Ellis, Vasileios Baltatzis, Arjun Nair, Loïc Le Folgoc, Sujal Desai, Ben Glocker, Julia A. Schnabel
2021	—	`conf`	The Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data. iMIMIC/TDA4MedicalData@MICCAI Vasileios Baltatzis, Loïc Le Folgoc, Sam Ellis, Octavio E. Martinez Manzanera, Kyriaki-Margarita Bintsi, Arjun Nair, Sujal Desai, Ben Glocker, Julia A. Schnabel
2021	J	`jnl`	The Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data. CoRR Vasileios Baltatzis, Loïc Le Folgoc, Sam Ellis, Octavio E. Martinez Manzanera, Kyriaki-Margarita Bintsi, Arjun Nair, Sujal Desai, Ben Glocker, Julia A. Schnabel
2021	—	`conf`	The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification. PRIME@MICCAI Vasileios Baltatzis, Kyriaki-Margarita Bintsi, Loïc Le Folgoc, Octavio E. Martinez Manzanera, Sam Ellis, Arjun Nair, Sujal Desai, Ben Glocker, Julia A. Schnabel
2021	J	`jnl`	The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification. CoRR Vasileios Baltatzis, Kyriaki-Margarita Bintsi, Loïc Le Folgoc, Octavio E. Martinez Manzanera, Sam Ellis, Arjun Nair, Sujal Desai, Ben Glocker, Julia A. Schnabel
2021	J	`jnl`	Uncertainty quantification in non-rigid image registration via stochastic gradient Markov chain Monte Carlo. CoRR Daniel Grzech, Mohammad Farid Azampour, Huaqi Qiu, Ben Glocker, Bernhard Kainz, Loïc Le Folgoc
2020	J	`jnl`	Bayesian Sampling Bias Correction: Training with the Right Loss Function. CoRR Loïc Le Folgoc, Vasileios Baltatzis, Amir Alansary, Sujal Desai, Anand Devaraj, Sam Ellis, Octavio E. Martinez Manzanera, Fahdi Kanavati, Arjun Nair, Julia A. Schnabel, Ben Glocker
2020	J	`jnl`	Explainable Anatomical Shape Analysis Through Deep Hierarchical Generative Models. IEEE Trans. Medical Imaging Carlo Biffi, Juan J. Cerrolaza, Giacomo Tarroni, Wenjia Bai, Antonio de Marvao, Ozan Oktay, Christian Ledig, Loïc Le Folgoc, Konstantinos Kamnitsas, Georgia Doumou, Jinming Duan, Sanjay K. Prasad, Stuart A. Cook, Declan P. O'Regan, Daniel Rueckert
2020	—	`conf`	Geometric Deep Learning for Post-Menstrual Age Prediction Based on the Neonatal White Matter Cortical Surface. UNSURE/GRAIL@MICCAI Vitalis Vosylius, Andy Wang, Cemlyn Waters, Alexey Zakharov, Francis Ward, Loïc Le Folgoc, John Cupitt, Antonios Makropoulos, Andreas Schuh, Daniel Rueckert, Amir Alansary
2020	J	`jnl`	Geometric Deep Learning for Post-Menstrual Age Prediction based on the Neonatal White Matter Cortical Surface. CoRR Vitalis Vosylius, Andy Wang, Cemlyn Waters, Alexey Zakharov, Francis Ward, Loïc Le Folgoc, John Cupitt, Antonios Makropoulos, Andreas Schuh, Daniel Rueckert, Amir Alansary
2020	—	`conf`	Image Registration via Stochastic Gradient Markov Chain Monte Carlo. UNSURE/GRAIL@MICCAI Daniel Grzech, Bernhard Kainz, Ben Glocker, Loïc Le Folgoc
2020	A*	`conf`	Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty. NeurIPS Miguel Monteiro, Loïc Le Folgoc, Daniel Coelho de Castro, Nick Pawlowski, Bernardo Marques, Konstantinos Kamnitsas, Mark van der Wilk, Ben Glocker
2020	J	`jnl`	Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty. CoRR Miguel Monteiro, Loïc Le Folgoc, Daniel Coelho de Castro, Nick Pawlowski, Bernardo Marques, Konstantinos Kamnitsas, Mark van der Wilk, Ben Glocker
2019	—	`conf`	Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing. IPMI Loïc Le Folgoc, Daniel Coelho de Castro, Jeremy Tan, Bishesh Khanal, Konstantinos Kamnitsas, Ian Walker, Amir Alansary, Ben Glocker
2019	J	`jnl`	Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing. CoRR Loïc Le Folgoc, Daniel Coelho de Castro, Jeremy Tan, Bishesh Khanal, Konstantinos Kamnitsas, Ian Walker, Amir Alansary, Ben Glocker
2019	—	`conf`	Deep Learning for Cardiac Motion Estimation: Supervised vs. Unsupervised Training. STACOM@MICCAI Huaqi Qiu, Chen Qin, Loïc Le Folgoc, Benjamin Hou, Jo Schlemper, Daniel Rueckert
2019	J	`jnl`	Evaluating reinforcement learning agents for anatomical landmark detection. Medical Image Anal. Amir Alansary, Ozan Oktay, Yuanwei Li, Loïc Le Folgoc, Benjamin Hou, Ghislain Vaillant, Konstantinos Kamnitsas, Athanasios Vlontzos, Ben Glocker, Bernhard Kainz, Daniel Rueckert
2019	J	`jnl`	Explainable Shape Analysis through Deep Hierarchical Generative Models: Application to Cardiac Remodeling. CoRR Carlo Biffi, Juan J. Cerrolaza, Giacomo Tarroni, Wenjia Bai, Ozan Oktay, Loïc Le Folgoc, Konstantinos Kamnitsas, Antonio de Marvao, Georgia Doumou, Jinming Duan, Sanjay K. Prasad, Stuart A. Cook, Declan P. O'Regan, Daniel Rueckert
2018	J	`jnl`	Attention U-Net: Learning Where to Look for the Pancreas. CoRR Ozan Oktay, Jo Schlemper, Loïc Le Folgoc, Matthew C. H. Lee, Mattias P. Heinrich, Kazunari Misawa, Kensaku Mori, Steven G. McDonagh, Nils Y. Hammerla, Bernhard Kainz, Ben Glocker, Daniel Rueckert
2018	—	`conf`	Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents. MICCAI (1) Amir Alansary, Loïc Le Folgoc, Ghislain Vaillant, Ozan Oktay, Yuanwei Li, Wenjia Bai, Jonathan Passerat-Palmbach, Ricardo Guerrero, Konstantinos Kamnitsas, Benjamin Hou, Steven McDonagh, Ben Glocker, Bernhard Kainz, Daniel Rueckert
2018	J	`jnl`	Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents. CoRR Amir Alansary, Loïc Le Folgoc, Ghislain Vaillant, Ozan Oktay, Yuanwei Li, Wenjia Bai, Jonathan Passerat-Palmbach, Ricardo Guerrero, Konstantinos Kamnitsas, Benjamin Hou, Steven G. McDonagh, Ben Glocker, Bernhard Kainz, Daniel Rueckert
2018	A*	`conf`	Semi-Supervised Learning via Compact Latent Space Clustering. ICML Konstantinos Kamnitsas, Daniel Coelho de Castro, Loïc Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya V. Nori
2018	J	`jnl`	Semi-Supervised Learning via Compact Latent Space Clustering. CoRR Konstantinos Kamnitsas, Daniel Coelho de Castro, Loïc Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya V. Nori
2017	J	`jnl`	Quantifying Registration Uncertainty With Sparse Bayesian Modelling. IEEE Trans. Medical Imaging Loïc Le Folgoc, Hervé Delingette, Antonio Criminisi, Nicholas Ayache
2017	J	`jnl`	Sparse Bayesian registration of medical images for self-tuning of parameters and spatially adaptive parametrization of displacements. Medical Image Anal. Loïc Le Folgoc, Hervé Delingette, Antonio Criminisi, Nicholas Ayache
2017	—	`conf`	Spectral Kernels for Probabilistic Analysis and Clustering of Shapes. IPMI Loïc Le Folgoc, Aditya V. Nori, Antonio Criminisi
2016	—	`conf`	Lifted Auto-Context Forests for Brain Tumour Segmentation. BrainLes@MICCAI Loïc Le Folgoc, Aditya V. Nori, Siddharth Ancha, Antonio Criminisi
2015	—	`—`	Statistical learning for image-based personalization of cardiac models. (Apprentissage statistique pour la personnalisation de modèles cardiaques à partir de données d'imagerie). Loïc Le Folgoc
2014	—	`conf`	Confidence-Based Training for Clinical Data Uncertainty in Image-Based Prediction of Cardiac Ablation Targets. MCV Rocío Cabrera Lozoya, Ján Margeta, Loïc Le Folgoc, Yuki Komatsu, Benjamin Berte, Jatin Relan, Hubert Cochet, Michel Haïssaguerre, Pierre Jaïs, Nicholas Ayache, Maxime Sermesant
2014	—	`conf`	Evaluation of Personalised Canine Electromechanical Models. STACOM Sophie Giffard-Roisin, Stéphanie Marchesseau, Loïc Le Folgoc, Hervé Delingette, Maxime Sermesant
2014	—	`conf`	Sparse Bayesian Registration. MICCAI (1) Loïc Le Folgoc, Hervé Delingette, Antonio Criminisi, Nicholas Ayache
2012	—	`conf`	Current-Based 4D Shape Analysis for the Mechanical Personalization of Heart Models. MCV Loïc Le Folgoc, Hervé Delingette, Antonio Criminisi, Nicholas Ayache