Hofmann, Thomas

Machine learning for real-time prediction of complications in critical care: a retrospective study

Meyer, A., Zverinski, D., Pfahringer, B., Kempfert, J., Kuehne, T., Sündermann, S. H., Stamm, C., Hofmann, T., Falk, V., & Eickhoff, C. (2018) · The Lancet Respiratory Medicine

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 350

Cosmological constraints with deep learning from KiDS-450 weak lensing maps

Fluri, J., Kacprzak, T., Lucchi, A., Refregier, A., Amara, A., Hofmann, T., & Schneider, A. (2019) · Physical Review D

Cosmology and Gravitation TheoriesGalaxies: Formation, Evolution, Phenomena

Cited by 151

Hyperbolic Entailment Cones for Learning Hierarchical Embeddings

Ganea, O.-E., Bécigneul, G., & Hofmann, T. (2018) · arXiv

Advanced Graph Neural NetworksTopological and Geometric Data Analysis

Cited by 115

Cosmological constraints from noisy convergence maps through deep learning

Fluri, J., Kacprzak, T., Refregier, A., Amara, A., Lucchi, A., & Hofmann, T. (2018) · Physical Review D

Cosmology and Gravitation TheoriesGalaxies: Formation, Evolution, Phenomena

Cited by 83

OpenFilter: A Framework to Democratize Research Access to Social Media AR Filters

Riccio, P., Psomas, B., Galati, F., Escolano, F., Hofmann, T., & Oliver, N. (2022) · Advances in Neural Information Processing Systems 35

Augmented Reality ApplicationsAcademic Publishing and Open Access

Cited by 8