Ellipsoidal Multiple Instance Learning. - Gabriel Krummenacher; Cheng Soon Ong; Joachim M. Buhmann (ICML (2), 2013)

Near-optimal experimental design for model selection in systems biology. - Alberto Giovanni Busetto; Alain Hauser; Gabriel Krummenacher; Mikael Sunnåker; Sotiris Dimopoulos; Cheng Soon Ong; Jörg Stelling; Joachim M. Buhmann (Bioinform., 2013)

Fast and Robust Least Squares Estimation in Corrupted Linear Models. - Brian McWilliams; Gabriel Krummenacher; Mario Lucic; Joachim M. Buhmann (NIPS, 2014)

Scalable Adaptive Stochastic Optimization Using Random Projections. - Gabriel Krummenacher; Brian McWilliams; Yannic Kilcher; Joachim M. Buhmann; Nicolai Meinshausen (NIPS, 2016)

Scalable and Robust Supervised Learning Through Random Approximations. - Gabriel Krummenacher (2016)

Wheel Defect Detection With Machine Learning. - Gabriel Krummenacher; Cheng Soon Ong; Stefan Koller; Seijin Kobayashi; Joachim M. Buhmann (IEEE Trans. Intell. Transp. Syst., 2018)

SPINDLE: End-to-end learning from EEG/EMG to extrapolate animal sleep scoring across experimental settings, labs and species. - Ðorðe Miladinovic; Christine Muheim; Stefan Bauer; Andrea Spinnler; Daniela Noain; Mojtaba Bandarabadi; Benjamin Gallusser; Gabriel Krummenacher; Christian R. Baumann; Antoine Adamantidis; Steven A. Brown; Joachim M. Buhmann (PLoS Comput. Biol., 2019)