Sebastian Pölsterl

According to our database, Sebastian Pölsterl authored at least 36 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

From Barlow Twins to Triplet Training: Differentiating Dementia with Limited Data.

Yitong Li, Tom Nuno Wolf, Sebastian Pölsterl, Igor Yakushev, Dennis M. Hedderich, Christian Wachinger

CoRR, 2024

Keep the Faith: Faithful Explanations in Convolutional Neural Networks for Case-Based Reasoning.

Tom Nuno Wolf, Fabian Bongratz, Anne-Marie Rickmann, Sebastian Pölsterl, Christian Wachinger

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Don't PANIC: Prototypical Additive Neural Network for Interpretable Classification of Alzheimer's Disease.

Tom Nuno Wolf, Sebastian Pölsterl, Christian Wachinger

Proceedings of the Information Processing in Medical Imaging, 2023

2022

DAFT: A universal module to interweave tabular data and 3D images in CNNs.

Tom Nuno Wolf, Sebastian Pölsterl, Christian Wachinger, Alzheimer's Disease Neuroimaging Initiative, Australian Imaging Biomarkers Lifestyle flagship study of ageing

NeuroImage, 2022

CASHformer: Cognition Aware SHape Transformer for Longitudinal Analysis.

Ignacio Sarasua, Sebastian Pölsterl, Christian Wachinger

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Joint Reconstruction and Parcellation of Cortical Surfaces.

Anne-Marie Rickmann, Fabian Bongratz, Sebastian Pölsterl, Ignacio Sarasua, Christian Wachinger

Proceedings of the Machine Learning in Clinical Neuroimaging - 5th International Workshop, 2022

Is a PET All You Need? A Multi-modal Study for Alzheimer's Disease Using 3D CNNs.

Marla Narazani, Ignacio Sarasua, Sebastian Pölsterl, Aldana Lizarraga, Igor Yakushev, Christian Wachinger

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Vox2Cortex: Fast Explicit Reconstruction of Cortical Surfaces from 3D MRI Scans with Geometric Deep Neural Networks.

Fabian Bongratz, Anne-Marie Rickmann, Sebastian Pölsterl, Christian Wachinger

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Detect and correct bias in multi-site neuroimaging datasets.

Christian Wachinger, Anna Rieckmann, Sebastian Pölsterl

Medical Image Anal., 2021

Semi-Structured Deep Piecewise Exponential Models.

Philipp Kopper, Sebastian Pölsterl, Christian Wachinger, Bernd Bischl, Andreas Bender, David Rügamer

Proceedings of AAAI Symposium on Survival Prediction, 2021

TransforMesh: A Transformer Network for Longitudinal Modeling of Anatomical Meshes.

Ignacio Sarasua, Sebastian Pölsterl, Christian Wachinger

Proceedings of the Machine Learning in Medical Imaging - 12th International Workshop, 2021

Alzheimer's Disease Diagnosis via Deep Factorization Machine Models.

Raphael Ronge, Kwangsik Nho, Christian Wachinger, Sebastian Pölsterl

Proceedings of the Machine Learning in Medical Imaging - 12th International Workshop, 2021

Combining 3D Image and Tabular Data via the Dynamic Affine Feature Map Transform.

Sebastian Pölsterl, Tom Nuno Wolf, Christian Wachinger

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Scalable, Axiomatic Explanations of Deep Alzheimer's Diagnosis from Heterogeneous Data.

Sebastian Pölsterl, Christina Aigner, Christian Wachinger

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Estimation of Causal Effects in the Presence of Unobserved Confounding in the Alzheimer's Continuum.

Sebastian Pölsterl, Christian Wachinger

Proceedings of the Information Processing in Medical Imaging, 2021

2020

'Squeeze & excite' guided few-shot segmentation of volumetric images.

Abhijit Guha Roy, Shayan Siddiqui, Sebastian Pölsterl, Nassir Navab, Christian Wachinger

Medical Image Anal., 2020

scikit-survival: A Library for Time-to-Event Analysis Built on Top of scikit-learn.

Sebastian Pölsterl

J. Mach. Learn. Res., 2020

Controlling for Unknown Confounders in Neuroimaging.

Sebastian Pölsterl, Christian Wachinger

CoRR, 2020

Adversarial Learned Molecular Graph Inference and Generation.

Sebastian Pölsterl, Christian Wachinger

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Bayesian Neural Networks for Uncertainty Estimation of Imaging Biomarkers.

Jyotirmay Senapati, Abhijit Guha Roy, Sebastian Pölsterl, Daniel Gutmann, Sergios Gatidis, Christopher Schlett, Annette Peters, Fabian Bamberg, Christian Wachinger

Proceedings of the Machine Learning in Medical Imaging - 11th International Workshop, 2020

Recalibration of Neural Networks for Point Cloud Analysis.

Ignacio Sarasua, Sebastian Pölsterl, Christian Wachinger

Proceedings of the 8th International Conference on 3D Vision, 2020

2019

Likelihood-Free Inference and Generation of Molecular Graphs.

Sebastian Pölsterl, Christian Wachinger

CoRR, 2019

BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learning.

Abhijit Guha Roy, Shayan Siddiqui, Sebastian Pölsterl, Nassir Navab, Christian Wachinger

CoRR, 2019

A Wide and Deep Neural Network for Survival Analysis from Anatomical Shape and Tabular Clinical Data.

Sebastian Pölsterl, Ignacio Sarasua, Benjamín Gutiérrez-Becker, Christian Wachinger

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Quantifying Confounding Bias in Neuroimaging Datasets with Causal Inference.

Christian Wachinger, Benjamín Gutiérrez-Becker, Anna Rieckmann, Sebastian Pölsterl

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

An AutoML Approach for the Prediction of Fluid Intelligence from MRI-Derived Features.

Sebastian Pölsterl, Benjamín Gutiérrez-Becker, Ignacio Sarasua, Abhijit Guha Roy, Christian Wachinger

Proceedings of the Adolescent Brain Cognitive Development Neurocognitive Prediction, 2019

Prediction of Fluid Intelligence from T1-Weighted Magnetic Resonance Images.

Sebastian Pölsterl, Benjamín Gutiérrez-Becker, Ignacio Sarasua, Abhijit Guha Roy, Christian Wachinger

Proceedings of the Adolescent Brain Cognitive Development Neurocognitive Prediction, 2019

2017

Algorithms for Large-scale Learning from Heterogeneous Survival Data (Methoden des maschinellen Lernens zur Analyse von Überlebenszeiten basierend auf heterogenen Daten)

Sebastian Pölsterl

PhD thesis, 2017

2016

An Efficient Training Algorithm for Kernel Survival Support Vector Machines.

Sebastian Pölsterl, Nassir Navab, Amin Katouzian

CoRR, 2016

Survival analysis for high-dimensional, heterogeneous medical data: Exploring feature extraction as an alternative to feature selection.

Sebastian Pölsterl, Sailesh Conjeti, Nassir Navab, Amin Katouzian

Artif. Intell. Medicine, 2016

Automatic Detection of Non-Biological Artifacts in ECGs Acquired During Cardiac Computed Tomography.

Rustem Bekmukhametov, Sebastian Pölsterl, Thomas Allmendinger, Minh-Duc Doan, Nassir Navab

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

2015

Stratification of coronary artery disease patients for revascularization procedure based on estimating adverse effects.

Sebastian Pölsterl, Maneesh Singh, Amin Katouzian, Nassir Navab, Adnan Kastrati, Lance Ladic, Ali Kamen

BMC Medical Informatics Decis. Mak., 2015

Fast Training of Support Vector Machines for Survival Analysis.

Sebastian Pölsterl, Nassir Navab, Amin Katouzian

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

2011

Relative location of CT slices on axial axis.

Franz Graf, Hans-Peter Kriegel, Matthias Schubert, Sebastian Pölsterl, Alexander Cavallaro

Dataset, July, 2011

2D Image Registration in CT Images Using Radial Image Descriptors.

Franz Graf, Hans-Peter Kriegel, Matthias Schubert, Sebastian Pölsterl, Alexander Cavallaro

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011, 2011

2010

Odefy -- From discrete to continuous models.

Jan Krumsiek, Sebastian Pölsterl, Dominik M. Wittmann, Fabian J. Theis

BMC Bioinform., 2010