Odefy – From discrete to continuous models. - Jan Krumsiek; Sebastian Pölsterl; Dominik M. Wittmann; Fabian J. Theis (BMC Bioinform., 2010)

2D Image Registration in CT Images Using Radial Image Descriptors. - Franz Graf 001; Hans-Peter Kriegel; Matthias Schubert; Sebastian Pölsterl; Alexander Cavallaro (MICCAI (2), 2011)

Relative location of CT slices on axial axis. - Franz Graf 001; Hans-Peter Kriegel; Matthias Schubert; Sebastian Pölsterl; Alexander Cavallaro (UCI Machine Learning Repository, 2011)

Fast Training of Support Vector Machines for Survival Analysis. - Sebastian Pölsterl; Nassir Navab; Amin Katouzian (ECML/PKDD (2), 2015)

Stratification of coronary artery disease patients for revascularization procedure based on estimating adverse effects. - Sebastian Pölsterl; Maneesh Singh 001; Amin Katouzian; Nassir Navab; Adnan Kastrati; Lance Ladic; Ali Kamen (BMC Medical Informatics Decis. Mak., 2015)

Automatic Detection of Non-Biological Artifacts in ECGs Acquired During Cardiac Computed Tomography. - Rustem Bekmukhametov; Sebastian Pölsterl; Thomas Allmendinger; Minh-Duc Doan; Nassir Navab (ECML/PKDD (3), 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)

An Efficient Training Algorithm for Kernel Survival Support Vector Machines. - Sebastian Pölsterl; Nassir Navab; Amin Katouzian (CoRR, 2016)

Algorithms for Large-scale Learning from Heterogeneous Survival Data (Methoden des maschinellen Lernens zur Analyse von Überlebenszeiten basierend auf heterogenen Daten) - Sebastian Pölsterl (2017)

Prediction of Fluid Intelligence from T1-Weighted Magnetic Resonance Images. - Sebastian Pölsterl; Benjamín Gutiérrez-Becker; Ignacio Sarasua; Abhijit Guha Roy; Christian Wachinger (ABCD-NP@MICCAI, 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 (ABCD-NP@MICCAI, 2019)

Quantifying Confounding Bias in Neuroimaging Datasets with Causal Inference. - Christian Wachinger; Benjamín Gutiérrez-Becker; Anna Rieckmann; Sebastian Pölsterl (MICCAI (4), 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 (PKDD/ECML Workshops (1), 2019)

BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learning. - Abhijit Guha Roy; Shayan Siddiqui; Sebastian Pölsterl; Nassir Navab; Christian Wachinger (CoRR, 2019)

Likelihood-Free Inference and Generation of Molecular Graphs. - Sebastian Pölsterl; Christian Wachinger (CoRR, 2019)

Recalibration of Neural Networks for Point Cloud Analysis. - Ignacio Sarasua; Sebastian Pölsterl; Christian Wachinger (3DV, 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 (MLMI@MICCAI, 2020)

Adversarial Learned Molecular Graph Inference and Generation. - Sebastian Pölsterl; Christian Wachinger (ECML/PKDD (2), 2020)

Controlling for Unknown Confounders in Neuroimaging. - Sebastian Pölsterl; Christian Wachinger (CoRR, 2020)

scikit-survival: A Library for Time-to-Event Analysis Built on Top of scikit-learn. - Sebastian Pölsterl (J. Mach. Learn. Res., 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)

Estimation of Causal Effects in the Presence of Unobserved Confounding in the Alzheimer's Continuum. - Sebastian Pölsterl; Christian Wachinger (IPMI, 2021)

Scalable, Axiomatic Explanations of Deep Alzheimer's Diagnosis from Heterogeneous Data. - Sebastian Pölsterl; Christina Aigner; Christian Wachinger (MICCAI (3), 2021)

Combining 3D Image and Tabular Data via the Dynamic Affine Feature Map Transform. - Sebastian Pölsterl; Tom Nuno Wolf; Christian Wachinger (MICCAI (5), 2021)

Alzheimer's Disease Diagnosis via Deep Factorization Machine Models. - Raphael Ronge; Kwangsik Nho; Christian Wachinger; Sebastian Pölsterl (MLMI@MICCAI, 2021)

TransforMesh: A Transformer Network for Longitudinal Modeling of Anatomical Meshes. - Ignacio Sarasua; Sebastian Pölsterl; Christian Wachinger (MLMI@MICCAI, 2021)

Semi-Structured Deep Piecewise Exponential Models. - Philipp Kopper; Sebastian Pölsterl; Christian Wachinger; Bernd Bischl; Andreas Bender 001; David Rügamer (SPACA, 2021)

Detect and correct bias in multi-site neuroimaging datasets. - Christian Wachinger; Anna Rieckmann; Sebastian Pölsterl (Medical Image Anal., 2021)

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 (CVPR, 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 (MICCAI (1), 2022)

Joint Reconstruction and Parcellation of Cortical Surfaces. - Anne-Marie Rickmann; Fabian Bongratz; Sebastian Pölsterl; Ignacio Sarasua; Christian Wachinger (MLCN@MICCAI, 2022)

CASHformer: Cognition Aware SHape Transformer for Longitudinal Analysis. - Ignacio Sarasua; Sebastian Pölsterl; Christian Wachinger (MICCAI (1), 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)

Don't PANIC: Prototypical Additive Neural Network for Interpretable Classification of Alzheimer's Disease. - Tom Nuno Wolf; Sebastian Pölsterl; Christian Wachinger (IPMI, 2023)

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 (AAAI, 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 (MIDL, 2024)