Constructing Shape Spaces from a Topological Perspective. - Christoph D. Hofer; Roland Kwitt; Marc Niethammer; Yvonne Höller; Eugen Trinka; Andreas Uhl (IPMI, 2017)

Simple domain adaptation for cross-dataset analyses of brain MRI data. - Christoph D. Hofer; Roland Kwitt; Yvonne Höller; Eugen Trinka; Andreas Uhl (ISBI, 2017)

Deep Learning with Topological Signatures. - Christoph D. Hofer; Roland Kwitt; Marc Niethammer; Andreas Uhl (NIPS, 2017)

Connectivity-Optimized Representation Learning via Persistent Homology. - Christoph D. Hofer; Roland Kwitt; Marc Niethammer; Mandar Dixit (ICML, 2019)

Graph Filtration Learning. - Christoph D. Hofer; Roland Kwitt; Marc Niethammer (CoRR, 2019)

Learning Representations of Persistence Barcodes. - Christoph D. Hofer; Roland Kwitt; Marc Niethammer (J. Mach. Learn. Res., 2019)

Topologically Densified Distributions. - Christoph D. Hofer; Florian Graf; Marc Niethammer; Roland Kwitt (ICML, 2020)

Graph Filtration Learning. - Christoph D. Hofer; Florian Graf; Bastian Rieck; Marc Niethammer; Roland Kwitt (ICML, 2020)

An empirical assessment of appearance descriptors applied to MRI for automated diagnosis of TLE and MCI. - Christoph D. Hofer; Roland Kwitt; Yvonne Höller; Eugen Trinka; Andreas Uhl (Comput. Biol. Medicine, 2020)

Prediction of Cognitive Decline in Temporal Lobe Epilepsy and Mild Cognitive Impairment by EEG, MRI, and Neuropsychology. - Yvonne Höller; Kevin Butz; Aljoscha Thomschewski; Elisabeth Schmid; Christoph D. Hofer; Andreas Uhl; Arne C. Bathke; Wolfgang Staffen; Raffaele Nardone; Fabian Schwimmbeck; Markus Leitinger; Georgi Kuchukhidze; et al. (Comput. Intell. Neurosci., 2020)

Dissecting Supervised Constrastive Learning. - Florian Graf; Christoph D. Hofer; Marc Niethammer; Roland Kwitt (ICML, 2021)

Topological Attention for Time Series Forecasting. - Sebastian Zeng; Florian Graf; Christoph D. Hofer; Roland Kwitt (NeurIPS, 2021)