PhD degree - Public Defence: Lars Skaaret-Lund, Fakultet for kjemi, bioteknologi og matvitenskap (KBM) forsvarer sin ph.d.-avhandling «Sparsom, usikkerhetsbevisst og forklarbar dyp læring ved hjelp av latente binære bayesianske nevrale nettverk» torsdag 3. september, 2026.
English title of thesis:
Sparse, Uncertainty-Aware, and Explainable Deep Learning via Latent Binary Bayesian Neural Networks
Norwegian title of the thesis:
Sparsom, usikkerhetsbevisst og forklarbar dyp læring ved hjelp av latente binære bayesianske nevrale nettverk.
Prescribed subject of the trial lecture (Approved):
Sparse Identification of Nonlinear Dynamics (SINDy): Principles and Basic Methods, with Applications to the Life Sciences. The trial lecture was held on August 14, 2026.
Evaluation committee - trial lecture:
Associate Professor Kathrine Frey Frøslie, KBM, NMBU
Professor Kristian Liland, REALTEK, NMBU
Professor Thore Egeland, KBM, NMBU (Administrator)
Time and place for the public defence:
Thursday September 3rd 2026, at 12.15.
The defence will be held at NMBU in U224, Urbygningen, NMBU.
Evaluation committee:
First opponent: Professor Kevin Burke, School of Medicine, University of Limerick, Limerick, Ireland
Second opponent: Professor Helge Langseth, Department of Computer Science, Faculty og Information Technology and Electrical Engineering, Norwegian University of Science and Technology, Trondheim, Norway
Committee coordinator: Professor Thore Egeland, Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, Norway
Supervisors:
Main supervisor:
Associate Professor Aliaksandr Hubin, Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås
Co-supervisor:
Professor Solve Sæbø, Norwegian University of Life Sciences, Ås
The doctoral thesis is available for public review.
For access to this thesis please send an email to: phd-kbm@nmbu.no
Thesis number 2026:70; ISSN 1894-6402; ISBN 978-82-575-2388-6