
About
August Arnstad is a Doctoral Research Fellow at the University of Oslo's Department of Mathematics, affiliated with the Faculty of Mathematics and Natural Sciences. His research focuses on Bayesian approaches to sparsification and pruning in neural networks, emphasizing prior specifications and algorithmic efficiency.
Education: Master's in Industrial Mathematics (2024) from NTNU, Trondheim. His PhD project explores sparse models in machine learning from a Bayesian perspective, supervised by Prof. Geir Storvik (UiO), Postdoc Leiv Rønneberg (UiO), and Prof. Fred Godtliebsen (UiT Arctic University).
Research interests include statistical modeling, Bayesian inference techniques, and applications in neural networks. No publications are listed in the provided data.
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