Hearables in Hearing Care: Discovering Usage Patterns Through IoT Devices. - Benjamin Johansen; Yannis Paul Raymond Flet-Berliac; Maciej Jan Korzepa; Per Sandholm; Niels Henrik Pontoppidan; Michael Kai Petersen; Jakob Eg Larsen (HCI (9), 2017)

Inferring User Intents from Motion in Hearing Healthcare. - Benjamin Johansen; Maciej Jan Korzepa; Michael Kai Petersen; Niels Henrik Pontoppidan; Jakob Eg Larsen (UbiComp/ISWC Adjunct, 2018)

Learning Preferences and Soundscapes for Augmented Hearing. - Maciej Jan Korzepa; Benjamin Johansen; Michael Kai Petersen; Jan Larsen; Jakob Eg Larsen; Niels Henrik Pontoppidan (IUI Workshops, 2018)

Modeling User Intents as Context in Smartphone-connected Hearing Aids. - Maciej Jan Korzepa; Benjamin Johansen; Michael Kai Petersen; Jan Larsen; Jakob Eg Larsen; Niels Henrik Pontoppidan (UMAP (Adjunct Publication), 2018)

Personalizing the Fitting of Hearing Aids by Learning Contextual Preferences From Internet of Things Data. - Benjamin Johansen; Michael Kai Petersen; Maciej Jan Korzepa; Jan Larsen; Niels Henrik Pontoppidan; Jakob Eg Larsen (Comput., 2018)

Approximate Inference Turns Deep Networks into Gaussian Processes. - Mohammad Emtiyaz Khan; Alexander Immer; Ehsan Abedi; Maciej Korzepa (NeurIPS, 2019)

Simulation Environment for Guiding the Design of Contextual Personalization Systems in the Context of Hearing Aids. - Maciej Korzepa; Michael Kai Petersen; Jakob Eg Larsen; Morten Mørup (UMAP (Adjunct Publication), 2020)

Modelling Audiological Preferences using Federated Learning. - Tiberiu-Ioan Szatmari; Michael Kai Petersen; Maciej Jan Korzepa; Thanassis Giannetsos (UMAP (Adjunct Publication), 2020)

Improving predictions of Bayesian neural networks via local linearization. - Alexander Immer; Maciej Korzepa; Matthias Bauer 001 (CoRR, 2020)

Improving predictions of Bayesian neural nets via local linearization. - Alexander Immer; Maciej Korzepa; Matthias Bauer 001 (AISTATS, 2021)

The Bayesian Cut. - Petr Taborsky; Laurent Vermue; Maciej Korzepa; Morten Mørup (IEEE Trans. Pattern Anal. Mach. Intell., 2021)