Multi-View Self-Supervised Learning For Multivariate Variable-Channel Time Series. - Thea Brüsch; Mikkel N. Schmidt; Tommy S. Alstrøm (MLSP, 2023)

On convex conceptual regions in deep network representations. - Lenka Tetková; Thea Brüsch; Teresa Karen Scheidt; Fabian Martin Mager; Rasmus Ørtoft Aagaard; Jonathan Foldager; Tommy Sonne Alstrøm; Lars Kai Hansen (CoRR, 2023)

Explaining time series models using frequency masking. - Thea Brüsch; Kristoffer K. Wickstrøm; Mikkel N. Schmidt; Tommy S. Alstrøm; Robert Jenssen (CoRR, 2024)

Contrastive random lead coding for channel-agnostic self-supervision of biosignals. - Thea Brüsch; Mikkel N. Schmidt; Tommy S. Alstrøm (CoRR, 2024)

FLEXtime: Filterbank learning for explaining time series. - Thea Brüsch; Kristoffer K. Wickstrøm; Mikkel N. Schmidt; Robert Jenssen; Tommy S. Alstrøm (CoRR, 2024)

REPEAT: Improving Uncertainty Estimation in Representation Learning Explainability. - Kristoffer K. Wickstrøm; Thea Brüsch; Michael C. Kampffmeyer; Robert Jenssen (AAAI, 2025)

FreqRISE: Explaining time series using frequency masking. - Thea Brüsch; Kristoffer Knutsen Wickstrøm; Mikkel N. Schmidt; Tommy Sonne Alstrøm; Robert Jenssen (NLDL, 2025)