Main Conference

Venue: Aud. Cerebrum (U.08.316) in the MH2 building at University in Tromsø (UiT)

Tuesday 10.01.2023

08:45-09:15 - Registration
09:15-09:30 - Opening
09:30-10:15 - Keynote: Mihaela van der Schaar (Chair: Robert Jenssen)
10:15-10:45 - Coffee break
10:45-11:45 - Oral session* (Chair: Ahcene Boubekki)
10:45 - PLM-AS: Pre-trained Language Models Augmented with Scanpaths for Sentiment Classification, Duo Yang, Center for Language Technology, University of Copenhagen
11:05 -
Contradiction Detection in Financial Reports, Tobias Deußer, University of Bonn, Maren Pielka, Fraunhofer IAIS
11:25 -
Multi-lingual agents through multi-headed neural networks, Jonathan David Thomas, University of Bristol
11:45-12:45 - Lunch
12:45-14:35 - Industry event (
14:35-15:00 - Coffee break
15:00-17:00 - Diversity in AI (
17:00-18:00 - Finger food and networking
18:30 - Cable car trip: Discover Northern Lights at Fjellheisen

Wednesday 11.01.2023

09:00-09:45 - Keynote: Christian Igel (Chair: Sarina Thomas)
09:45-10:10 - Coffee break
10:10-11:30 - Oral session* (Chair: Arnt-Børre Salberg)
10:10 - Boundary Aware U-Net for Glacier Segmentation, Olac Fuentes, Department of Computer Science, The University of Texas at El Paso
10:30 -
Improved Imagery Throughput via Cascaded Uncertainty Pruning on U-Net++, Zifu Wang, KU Leuven ESAT(PSI)
10:50 -
Semi- and weak-supervised learning for Norwegian tree species detection, David Völgyes, Science and Technology AS
11:10 -
Improving Wind Speed Uncertainty Forecasts Using Recurrent Neural Networks, Juri Backes, University of Applied Sciences Hamburg (HAW)
11:30-12:30 - Lunch
12:30-13:10 - Oral session* (Chair: Alba Ordonez)
12:30 - Explainability in subgraphs-enhanced Graph Neural Networks, Michele Guerra, UiT the Arctic University of Norway
12:50 -
A comparison between Tsetlin machines and deep neural networks in the context of recommendation systems, Karl Audun Borgersen, University of Agder
13:10-14:30 - Poster session 1 & Coffee
14:30-16:10 - Oral session* (Chair: Filippo Bianchi)
14:30 - FastDTI: Drug-Target Interaction Prediction using Multimodality and Transformers, Maryam Tavakol, Eindhoven University of Technology.
14:50 -
Efficient Self-Supervision using Patch-based Contrastive Learning for Histopathology Image Segmentation, Nicklas Boserup, Department of Computer Science, University of Copenhagen
15:10 -
Signal and Visual Approaches for Parkinson's Disease Detection from Spiral Drawings, Cristina Luna-Jiménez, Universidad Politécnica de Madrid
15:30 -
Reducing Annotator's Burden: Cross-Pseudo Supervision for Brain Tumor Segmentation, Lidia Luque, Center for Computational Radiology and Artificial Intelligence (CRAI), Oslo University Hospital
15:50 -
Contrastive learning for unsupervised medical image clustering and reconstruction, Matteo Ferrante, University of Rome, Tor Vergata
19:00 - Conference dinner at Scandic Ishavshotel (Google Maps)

Thursday 12.01.2023

09:00-09:45 - Keynote: Polina Golland (Chair: Michael Kampffmeyer)
09:45-10:10 - Coffee break
10:10-11:30 - Oral session* (Chair: Signe Riemer-Sørensen)
10:10 - RIDDLE: Rule Induction with Deep Learning, Cosimo Persia, University of Bergen
10:30 -
Questionable Practices in Methodological Deep Learning Research, Daniel J. Trosten, UiT Machine Learning Group
10:50 -
Nearest Unitary and Toeplitz matrix techniques for adaptation of Deep Learning models in photonic FPGA, Georgios Agrafiotis, Centre for Research and Technology Hellas
11:10 -
Measuring Adversarial Robustness using a Voronoi-Epsilon Adversary, Ketil Malde, Institute of Marine Research and Department of Informatics, University of Bergen
11:30-12:30 - Lunch
12:30-13:10 - Oral session* (Chair: Narada Dilp Warakagoda)
12:30 - Using Mask R-CNN for Underwater Fish Instance Segmentation as Novel Objects: A Proof of Concept, I-Hao Chen, NORCE
12:50 -
A contrastive learning approach for individual re-identification in a wild fish population, Ørjan Langøy Olsen, University of Agder
13:10-14:00 - NORA panel discussion
14:00-15:20 - Poster session 2 & Coffee
15:20-15:40 - NORA competition
15:40-17:00 - Oral session* (Chair: Georgios Leontidis)
15:40 - Evaluating current state of monocular 3D pose models for golf, Christian Keilstrup Ingwersen, TrackMan A/S + Technical University of Denmark
16:00 -
Identifying and Mitigating Flaws of Deep Perceptual Similarity Metrics, Oskar Sjögren, Luleå University of Technology
16:20 -
Multi-modal data generation with a deep metric variational autoencoder, Josefine Vilsbøll Sundgaard, Technical University of Denmark & Novo Nordisk A/S
16:40 -
Interactive Scribble Segmentation, Mathias Michelsen Lowes, Jakob Lønborg Christensen and Bjørn Hansen, Technical University of Denmark
17:00 - Closing
17:30 - Visit at "The Science Centre of Northern Norway" (
Google Maps)

Poster session 1, Wednesday 11.01.2023 13:10-14:30

#1 3D Convolutional Masked Modelling Advances Lesion Classification in Axial T2w Prostate MRI*, Alvaro Fernandez-Quilez, Stavanger Medical Imaging Laboratory, Department of Radiology, Stavanger University Hospital
#2 Simplifying Clustering with Graph Neural Networks
*, Filippo Maria Bianchi, UiT the Arctic University of Norway and NORCE Norwegian Research Centre
#3 Dense FixMatch: a simple semi-supervised learning method for pixel-wise prediction tasks
*, Miquel Martí i Rabadán, Univrses AB, KTH Royal Institute of Technology
#4 Robin Pre-Training for the Deep Ritz Method
*, Marius Zeinhofer, Simula Research Laboratory
#5 Solving Partial Differential Equations with Nonlinear Conservation Laws Using Graph Neural Networks
*, Qing Li (University of Stavanger, Department of Energy and Petroleum, Group of Computational Engineering)
#6 Using deep convolutional neural networks to predict patients age based on ECGs from an independent test cohort
*, Bjørn-Jostein Singstad, Vestfold Hospital Trust and Simula Research Laboratory
#7 Automatic Postoperative Brain Tumor Segmentation with Limited Data using Transfer Learning and Triplet Attention
*, Jingpeng Li, Division of Radiology and Nuclear Medicine, Oslo University Hospital and Department of Physics, University of Oslo
#8 A Neural Network Explainer in the Wavelet Domain,
Stefan Kolek, Ludwig Maximilian University of Munich
#9 Attention-Based Deep Learning Methods for Predicting Gas Turbine Emissions,
Rebecca Potts, University of Aberdeen
#10 Sparsifying Bayesian neural networks with latent binary variables and normalizing flows,
Lars Skaaret-Lund, Norwegian University of Life Sciences
#11 Can a deep learning model trained to segment white matter hyperintensities (WMH) be used on patients that have combined WMH and stroke lesions?,
Martin Soria Røvang, CRAI
#12 Uncertainty Quantification with Tsetlin Machine Using Ideas from Deep Learning,
K. Darshana Abeyrathna, DNV
#13 ReSonet: Realistic Synthetic Social Networks with Graph Neural Networks,
Alex Davies, University of Bristol
#14 Learning from multimodal reference atlases: from single cells to patients,
Anastasia Litinetskaya, Helmholtz Center Munich
#15 Towards a More Data Efficient Sim2real Tactile Robotics Using Transfer Learning,
Matt Clifford, University of Bristol
#16 Segmentation of post-operative glioblastoma,
Ragnhild Holden Helland, SINTEF Digital / NTNU

Poster session 2, Thursday 12.01.2023 14:00-15:20

#2 Hybrid bayesian convolutional neural network object detection architectures for tracking small markers in automotive crashtest videos*, Felix Neubürger, University of Applied Science South Westphalia
#3 Learning to solve arithmetic problems with a virtual abacus
*, Alberto Testolin, University of Padova (Italy)
#4 Automatic Consistency Checking of Table and Text in Financial Documents
*, Tobias Deußer, University of Bonn & Fraunhofer IAIS
#5 Neural Tangent Kernel Beyond the Infinite-Width Limit: Effects of Depth and Initialization,
Mariia Selezniova, LMU Munich
#6 Viola-Unet: Voxels Intersecting along Orthogonal Levels Attention U-Net to Segment Intracerebral Haemorrhage Using CT Head Scans,
Bradley J MacIntosh, Oslo University Hospital (OUS)
#8 Towards Reliable AI: From Digital to Analog Hardware,
Adalbert Fono, LMU Munich
#9 A Visually-Assisted Hearing Aid System Based on Deep Learning,
Daniel Michelsanti, Oticon and Aalborg University
#10 Improving Performance of Brain-Age Prediction Using Transfer Learning from Masked Image Modeling,
Edvard Grødem, CRAI, Oslo University Hospital
#12 Deep Learning Based Automated Multi-Organ Segmentation in Lymphoma Patients using FDG PET/MRI Images,
Anum Masood, Norwegian University of Science and Technology (NTNU)
#13 Leveraging structured and unstructured speech for improving early dementia detection,
Daniel P Kumpik, University of Bristol
#14 Bayesian uncertainty estimation in neural network-based image classification,
Matteo Ferrante, University of Rome Tor Vergata
#16 Data Modelling for Digital Twins,
Boris Mocialov, Aize
#17 Gradient-based labels from learning from small data
, Jonathan Erskine, University of Bristol

*Full length paper that will be included in the proceedings