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Department of Mathematics and Statistics jnm022@post.uit.no +4777645118 Tromsø

Jonas Nordhaug Myhre

Researcher / Machine Learning

  • Tejedor H Miguel Angel, Sigurd Hjerde, Jonas Nordhaug Myhre, Fred Godtliebsen :
    Evaluating Deep Q-Learning Algorithms for Controlling Blood Glucose in In Silico Type 1 Diabetes
    Diagnostics (Basel) 07. October 2023 ARKIV / DOI
  • Jonathan E Berezowski, Thomas Andre Haugland Johansen, Jonas Nordhaug Myhre, Fred Godtliebsen :
    Variable Depth Bayesian Neural Networks Using Reversible Jumps
    IEEE conference proceedings 2022 FULLTEKST / DOI
  • Sara Maria Björk, Jonas Nordhaug Myhre, Thomas Haugland Johansen :
    Simpler is Better: Spectral Regularization and Up-Sampling Techniques for Variational Autoencoders
    IEEE conference proceedings 2022 DOI
  • Isak Paasche Edvardsen, Anna Teterina, Thomas Haugland Johansen, Jonas Nordhaug Myhre, Fred Godtliebsen, Napat Limchaichana Bolstad :
    Automatic detection of the mental foramen for estimating mandibular cortical width in dental panoramic radiographs: the seventh survey of the Tromsø Study (Tromsø7) in 2015-2016
    Journal of International Medical Research 22. November 2022 ARKIV / DOI
  • Ahcene Boubekki, Jonas Nordhaug Myhre, Luigi Tommaso Luppino, Karl Øyvind Mikalsen, Arthur Revhaug, Robert Jenssen :
    Clinically relevant features for predicting the severity of surgical site infections
    IEEE journal of biomedical and health informatics 2021 ARKIV / FULLTEKST / DOI
  • Jonas Nordhaug Myhre, Miguel Angel Tejedor Hernandez, Ilkka Kalervo Launonen, Anas El Fathi, Fred Godtliebsen :
    In-silico evaluation of glucose regulation using policy gradient reinforcement learning for patients with type 1 diabetes mellitus
    Applied Sciences 11. September 2020 ARKIV / DOI
  • Jonas Nordhaug Myhre :
    Secant manifold constrained random projections - Improved cluster ensembles
    Proceedings of the International Joint Conference on Neural Networks 2018 DOI
  • Jonas Nordhaug Myhre, Fred Godtliebsen, Ilkka Kalervo Launonen, Susan Wei :
    CONTROLLING BLOOD GLUCOSE LEVELS IN PATIENTS WITH TYPE 1 DIABETES USING FITTED Q-ITERATIONS AND FUNCTIONAL FEATURES
    IEEE Signal Processing Society 2018 DOI
  • Jonas Nordhaug Myhre, Robert Jenssen, Karl Øyvind Mikalsen, Sigurd Løkse :
    Robust clustering using a kNN mode seeking ensemble
    Pattern Recognition 2017 ARKIV / FULLTEKST / PROSJEKT / DOI
  • Jonas Nordhaug Myhre, Michael C. Kampffmeyer, Robert Jenssen :
    Density ridge manifold traversal
    IEEE conference proceedings 2017 ARKIV / DOI
  • Jonas Nordhaug Myhre, Karl Øyvind Mikalsen, Sigurd Løkse, Robert Jenssen :
    Consensus Clustering Using kNN Mode Seeking
    Springer 2015 DOI
  • Matineh Shaker, Jonas Nordhaug Myhre, Deniz Erdogmus :
    Computationally Efficient Exact Calculation of Kernel Density Derivatives
    Journal of Signal Processing Systems 2014 DOI
  • Matineh Shaker, Jonas Nordhaug Myhre, M. Devrim Kaba, Deniz Erdogmus :
    Invertible nonlinear cluster unwrapping
    IEEE Workshop on Machine Learning for Signal Processing 2014 DOI
  • Robert Jenssen, Jonas Nordhaug Myhre :
    MIXTURE WEIGHT INFLUENCE ON KERNEL ENTROPY COMPONENT ANALYSIS AND SEMI-SUPERVISED LEARNING USING THE LASSO
    IEEE Signal Processing Society 2012 FULLTEKST / DOI
  • Erlend Winje, Tor-Arne Bjørn, Inger Hansen, Erling Meisingset, Atilla Haugen, Joachim Bernd Heppelmann et al.:
    Droner som FKT - bruk av droner som forebyggende tiltak i beitenæringen
    2023 ARKIV
  • Aksel Andreas Transeth, Lars Erik Flatner, Tomas Norvoll, Ahmed Kedir Mohammed, Asbjørn Berge, Gard Spreemann et al.:
    Kunstig intelligens skal gjøre flyplassens farligste område tryggere: – Vil fjerne de mest vanlige årsakene til uhellene
    20. December 2023 FULLTEKST / PROSJEKT
  • Miguel Angel Tejedor Hernandez, Jonas Nordhaug Myhre :
    Controlling Blood Glucose For Patients With Type 1 Diabetes Using Deep Reinforcement Learning - The Influence Of Changing The Reward Function
    2020
  • Miguel Angel Tejedor Hernandez, Jonas Nordhaug Myhre :
    Including T1D knowledge in deep reinforcement learning reduces hypoglycemia
    2020
  • Miguel Angel Tejedor Hernandez, Jonas Nordhaug Myhre :
    Controlling Blood Glucose For Patients With Type 1 Diabetes Using Deep Reinforcement Learning - The Influence Of Changing The Reward Function
    2020
  • Jonas Nordhaug Myhre, Miguel Angel Tejedor Hernandez, Ilkka Kalervo Launonen, Fred Godtliebsen :
    In-silico Evaluation of Type-1 Diabetes Closed-Loop Control using Deep Reinforcement Learning
    2019
  • Jonas Nordhaug Myhre, Miguel Angel Tejedor Hernandez, Ilkka Kalervo Launonen, Fred Godtliebsen :
    In-silico Evaluation of Trust Region Policy Optimization Reinforcement Learning for T1DM Closed-Loop Control
    2019
  • Phuong Ngo, Jonas Nordhaug Myhre, Fred Godtliebsen :
    Reinforcement Learning Algorithm for Patients with Type-1 Diabetes
    2017
  • Jonas Nordhaug Myhre, Robert Jenssen, Deniz Erdogmus, Matineh Shaker, M. Devrim Kaba :
    Geometric interpretation of density ridges.
    2016
  • Jonas Nordhaug Myhre, Michael C. Kampffmeyer, Robert Jenssen :
    Ambient space manifold learning using density ridges
    2016
  • Jonas Nordhaug Myhre, Robert Jenssen :
    MIXTURE WEIGHT INFLUENCE ON KERNEL ENTROPY COMPONENT ANALYSIS AND SEMI-SUPERVISED LEARNING USING THE LASSO
    2012

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