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Bilde av Godtliebsen, Fred
Bilde av Godtliebsen, Fred
Professor Institutt for matematikk og statistikk fred.godtliebsen@uit.no +4777644019 954 45388 Her finner du meg

Fred Godtliebsen

Stillingsbeskrivelse

Professor i statistikk. 

 

  • Iver Martinsen, David Wade, Fred Godtliebsen, Benjamin Ricaud :
    The 3-billion fossil question: How to automate classification of microfossils
    Artificial Intelligence in Geosciences 2024 ARKIV / DOI
  • Fred Godtliebsen, Eirik Myrvoll-Nilsen, Lasse Holmström :
    Comments on: Data integration via analysis of subspaces (DIVAS)
    Test (Madrid) 2024
  • Marit Dagny Kristine Jenssen, Elisa Salvi, Egil Andreas Fors, Ole Andreas Nilsen, Phuong Dinh Ngo, Miguel Angel Tejedor Hernandez m.fl.:
    Exploring Pain Reduction through Physical Activity: A Case Study of Seven Fibromyalgia Patients
    Bioengineering 2024 ARKIV / DOI
  • 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. oktober 2023 ARKIV / DOI
  • Phuong Ngo, Miguel Angel Tejedor Hernandez, Fred Godtliebsen :
    Data-Driven Robust Control Using Reinforcement Learning
    Applied Sciences 2022 FULLTEKST / ARKIV / DOI
  • Taridzo Fred Chomutare, Miguel Angel Tejedor Hernandez, Therese Olsen Svenning, Luis Marco Ruiz, Maryam Tayefi Nasrabadi, Karianne Fredenfeldt Lind m.fl.:
    Artificial Intelligence Implementation in Healthcare: A Theory-Based Scoping Review of Barriers and Facilitators
    International Journal of Environmental Research and Public Health (IJERPH) 2022 ARKIV / 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
  • 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
  • Maryam Tayefi, Phuong Ngo, Taridzo Chomutare, Hercules Dalianis, Elisa Salvi, Andrius Budrionis m.fl.:
    Challenges and opportunities beyond structured data in analysis of electronic health records
    Wiley Interdisciplinary Reviews: Computational Statistics 14. februar 2021 ARKIV / DOI
  • Thomas Haugland Johansen, Steffen Aagaard Sørensen, Kajsa Møllersen, Fred Godtliebsen :
    Instance Segmentation of Microscopic Foraminifera
    Applied Sciences 2021 ARKIV / DOI
  • Marit Dagny Kristine Jenssen, Per Atle Bakkevoll, Phuong Ngo, Andrius Budrionis, Asbjørn Johansen Fagerlund, Maryam Tayefi m.fl.:
    Machine Learning in Chronic Pain Research: A Scoping Review
    Applied Sciences 2021 ARKIV / DOI
  • Stig Uteng, Eduardo Quevedo, Gustavo M. Callico, Irene Castaño, Gregorio Carretero, Pablo Almeida m.fl.:
    Curve-Based Classification Approach for Hyperspectral Dermatologic Data Processing
    Sensors 2021 ARKIV / DOI
  • Stig Uteng, Thomas Haugland Johansen, Jose Ignacio Zaballos, Samuel Ortega, Lasse Holmström, Gustavo M. Callico m.fl.:
    Early Detection of Change by Applying Scale-Space Methodology to Hyperspectral Images
    Applied Sciences 2020 ARKIV / DOI
  • Miguel Angel Tejedor Hernandez, Ashenafi Zebene Woldaregay, Fred Godtliebsen :
    Reinforcement learning application in diabetes blood glucose control: A systematic review
    Artificial Intelligence in Medicine 2020 ARKIV / DOI
  • Phuong Ngo, Miguel Angel Tejedor Hernandez, Maryam Tayefi, Taridzo Chomutare, Fred Godtliebsen :
    Risk-Averse Food Recommendation Using Bayesian Feedforward Neural Networks for Patients with Type 1 Diabetes Doing Physical Activities
    Applied Sciences 2020 ARKIV / DOI
  • Kajsa Møllersen, Jon Yngve Hardeberg, Fred Godtliebsen :
    A probabilistic bag-to-class approach to multiple-instance learning
    Data 26. juni 2020 ARKIV / DOI
  • Taridzo Chomutare, Kassaye Yitbarek Yigzaw, Andrius Budrionis, Alexandra Makhlysheva, Fred Godtliebsen, Hercules Dalianis :
    De-identifying Swedish EHR text using public resources in the general domain
    Studies in Health Technology and Informatics 2020 ARKIV / DOI
  • Sebastian Andres Acuña Maldonado, Ida Sundvor Opstad, Fred Godtliebsen, Balpreet Singh Ahluwalia, Krishna Agarwal :
    Soft thresholding schemes for multiple signal classification algorithm
    Optics Express 2020 ARKIV / DOI
  • Samuel Ortega, Martin Halicek, Himar Fabelo, Rafael Camacho, Maria de La Luz Plaza, Fred Godtliebsen m.fl.:
    Hyperspectral imaging for the detection of glioblastoma tumor cells in H&E slides using convolution neural networks
    Sensors 30. mars 2020 ARKIV / DOI
  • Samuel Ortega, Martin Halicek, Himar Fabelo, Raul Guerra, Carlos Lopez, Marylene Lejaune m.fl.:
    Hyperspectral imaging and deep learning for the detection of breast cancer cells in digitized histological images
    Proceedings of SPIE, the International Society for Optical Engineering 2020 FULLTEKST / DOI
  • Giovanni Sebastiani, Stig Uteng, Fred Godtliebsen, Jan Polàk, Jan Brož :
    Estimation of Blood Glucose Concentration During Endurance Sports
    International Journal of Biology and Biomedical Engineering 2020 ARKIV / 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
  • Kristian Hindberg, Jan Hannig, Fred Godtliebsen :
    A novel scale-space approach for multinormality testing and the k-sample problem in the high dimension low sample size scenario
    PLOS ONE 2019 ARKIV / DOI
  • Thomas Haugland Johansen, Kajsa Møllersen, Samuel Ortega, Himar Fabelo, Aday Garcia, Gustavo Callico m.fl.:
    Recent advances in hyperspectral imaging for melanoma detection
    Wiley Interdisciplinary Reviews: Computational Statistics 2019 ARKIV / DOI
  • John S. Hammond, Fred Godtliebsen, Sonja Eriksson Steigen, I. Neil Guha, Judy Wyatt, Arthur Revhaug m.fl.:
    The effects of terlipressin and direct portacaval shunting on liver hemodynamics following 80% hepatectomy in the pig
    Clinical Science 2019 ARKIV / DOI
  • Phuong Ngo, Maryam Tayefi, Anne Torill Nordsletta, Fred Godtliebsen :
    Food recommendation using machine learning for physical activities in patients with type 1 diabetes
    Linköping Electronic Conference Proceedings 2019 ARKIV / FULLTEKST
  • Phuong Ngo, Susan Wei, Anna Holubova, Jan Muzik, Fred Godtliebsen :
    Reinforcement-Learning Optimal Control for Type-1 Diabetes
    IEEE (Institute of Electrical and Electronics Engineers) 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
  • David Wade, Fred Godtliebsen, Benjamin Ricaud, Iver Martinsen :
    A deep learning pipeline for automatic microfossil analysis and classification
    2024
  • Iver Martinsen, David Wade, Benjamin Ricaud, Fred Godtliebsen :
    A deep learning pipeline for automatic microfossil analysis and classification
    2024
  • Steffen Aagaard Sørensen, Eirik Myrvoll-Nilsen, Iver Martinsen, Fred Godtliebsen, Stamatia Galata, Juho Junttila m.fl.:
    Detection and identification of environmental faunal proxies in digital images and video footage from northern Norwegian fjords and coastal waters using deep learning object detection algorithms
    2024
  • Iver Martinsen, Benjamin Ricaud, David Wade, Fred Godtliebsen :
    Grouping microscopic fossils without labels using self-supervision
    2023
  • Fred Godtliebsen :
    Sparse networks in deep learning
    2023
  • Fred Godtliebsen :
    Trans-dimensional Bayesian Deep Learning
    2023
  • Fred Godtliebsen :
    Sparse Networks in Deep Learning
    2023
  • Eirik Myrvoll-Nilsen, Steffen Aagaard-Sørensen, Stamatia Galata, Thomas Haugland Johansen, Iver Martinsen, Morten Hald m.fl.:
    Automated classification of microscopic foraminifera
    2023
  • Eirik Myrvoll-Nilsen, Steffen Aagaard-Sørensen, Stamatia Galata, Thomas Haugland Johansen, Iver Martinsen, Morten Hald m.fl.:
    Automating object detection and classification of foraminifera
    2023
  • Iver Martinsen, Benjamin Ricaud, David Wade, Fred Godtliebsen :
    An efficient pipeline for microfossil analysis
    2023
  • Steffen Aagaard Sørensen, Eirik Myrvoll-Nilsen, Stamatia Galata, Thomas Haugland Johansen, Iver Martinsen, Morten Hald m.fl.:
    Automated image/video classification and object detection of foraminifera
    2023
  • David Wade, Iver Martinsen, Erik Anthonissen, Alex Cullum, Robert Williams, Fred Godtliebsen m.fl.:
    Species Classification Automation for Microfossil Photomicrograph Images
    2022
  • Iver Martinsen, David Wade, Fred Godtliebsen, Benjamin Ricaud :
    SCAMPI - Species Classification Automation for Microfossil Photomicrograph Images
    2022
  • Fred Godtliebsen, Steffen Aagaard Sørensen, Morten Hald :
    Automatisk overvåkning av havbunnen
    2022 FULLTEKST
  • Phuong Ngo, Eirik Årsand, Fred Godtliebsen :
    Toward A Personalized Decision Support System for Blood Glucose Management During and After Physical Activities in Patients with Type 1 Diabetes
    Diabetes Technology & Therapeutics 2020 FULLTEKST
  • Thomas Haugland Johansen, Kajsa Møllersen, Samuel Ortega, Himar Fabelo, Gustavo Callico, Fred Godtliebsen :
    Detecting skin cancer using hyperspectral images
    Advanced Science News 2020
  • Beatriz Martinez-Vega, Eduardo Quevedo, Raquel Leon, Himar Fabelo, Samuel Ortega, Gustavo M. Callico m.fl.:
    Statistics-based Classification Approach for Hyperspectral Dermatologic Data Processing
    2020
  • 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
  • Sebastian Andres Acuña Maldonado, G M A Mehedi Hussain, Fred Godtliebsen, Balpreet Singh Ahluwalia, Hoai Phuong Ha, Dilip K. Prasad m.fl.:
    Multiple Signal Classiflcation: Challenges on the Route from Millimeter Resolution to Nanometer Resolution
    2019
  • 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
  • Phuong D. Ngo, Fred Godtliebsen :
    Data-Driven Robust Control Using Reinforcement Learning
    2018
  • Phuong D. Ngo, Miguel Angel Tejedor Hernandez, Fred Godtliebsen :
    A Decision Support Tool for Optimal Control of Planet Temperature Using Reinforcement Learning
    2018

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