Fred Godtliebsen
Stillingsbeskrivelse
Professor i statistikk.
Fred Godtliebsen,
Eirik Myrvoll-Nilsen,
Lasse Holmström
:
Comments on: Data integration via analysis of subspaces (DIVAS)
Iver Martinsen,
David Wade,
Benjamin Ricaud,
Fred Godtliebsen
:
The 3-billion fossil question: How to automate classification of microfossils
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
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
Jonathan E Berezowski,
Thomas Andre Haugland Johansen,
Jonas Nordhaug Myhre,
Fred Godtliebsen
:
Variable Depth Bayesian Neural Networks Using Reversible Jumps
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
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
Phuong Ngo,
Miguel Angel Tejedor Hernandez,
Fred Godtliebsen
:
Data-Driven Robust Control Using Reinforcement Learning
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
Thomas Haugland Johansen,
Steffen Aagaard Sørensen,
Kajsa Møllersen,
Fred Godtliebsen
:
Instance Segmentation of Microscopic Foraminifera
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
Stig Uteng,
Eduardo Quevedo,
Gustavo M. Callico,
Irene Castaño,
Gregorio Carretero,
Pablo Almeida
m.fl.:
Curve-Based Classification Approach for Hyperspectral Dermatologic Data Processing
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
Miguel Angel Tejedor Hernandez,
Ashenafi Zebene Woldaregay,
Fred Godtliebsen
:
Reinforcement learning application in diabetes blood glucose control: A systematic review
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
Kajsa Møllersen,
Jon Yngve Hardeberg,
Fred Godtliebsen
:
A probabilistic bag-to-class approach to multiple-instance learning
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
Sebastian Andres Acuña Maldonado,
Ida Sundvor Opstad,
Fred Godtliebsen,
Balpreet Singh Ahluwalia,
Krishna Agarwal
:
Soft thresholding schemes for multiple signal classification algorithm
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
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
Giovanni Sebastiani,
Stig Uteng,
Fred Godtliebsen,
Jan Polàk,
Jan Brož
:
Estimation of Blood Glucose Concentration During Endurance Sports
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
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
Thomas Haugland Johansen,
Kajsa Møllersen,
Samuel Ortega,
Himar Fabelo,
Aday Garcia,
Gustavo Callico
m.fl.:
Recent advances in hyperspectral imaging for melanoma detection
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
Phuong Ngo,
Maryam Tayefi,
Anne Torill Nordsletta,
Fred Godtliebsen
:
Food recommendation using machine learning for physical activities in patients with type 1 diabetes
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
Iver Martinsen,
Fred Godtliebsen,
Steffen Aagaard Sørensen,
Eirik Myrvoll-Nilsen,
Samuel Ortega Sarmiento,
Miguel Angel Tejedor Hernandez
:
Are humans an AI uncertain about the same things?
2024
Iver Martinsen,
Fred Godtliebsen,
Benjamin Ricaud,
David Wade
:
The 3-billion fossil question
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
Fred Godtliebsen,
Steffen Aagaard Sørensen,
Morten Hald
:
Automatisk overvåkning av havbunnen
2022 FULLTEKST
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
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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