Program

From Finite Element Analysis to Self-Optimization: FRAME (Finite element Reasoning and AI-Agent Model Engine) and the Era of Agentic AI in Engineering

Mahish K. Guru, Vipul Gupta, Kartik Bali, Roland Aydin

Improved probabilistic regression using diffusion models

Carlo Kneissl, Christopher Bülte, Philipp Scholl, Gitta Kutyniok

Random Spiking Neural Networks are Stable and Spectrally Simple

Ernesto Araya, Massimiliano Datres, Gitta Kutyniok

Data Dowsing: Determining Data Collection Priorities

Ryan Marinelli

Mode Connectivity in Neural Quantum States

Vinicius Hernandes, Thomas Spriggs, Eliska Greplova

The Price of Robustness: Stable Classifiers Need Overparameterization

Jonas von Berg, Adalbert Fono, Massimiliano Datres, Sohir Maskey, Gitta Kutyniok

Flatness Has a Shape: Scalar Curvature and Functional Dimension in Neural Loss Landscapes

Johanna Marie Gegenfurtner

Learnable Masks for Time Series Explainability using Time-Frequency Representations

Theresa Dahl Frehr, Thea Brüsch, Tommy Sonne Alstrøm

GOGH: Correlation-Guided Orchestration of GPUs in Heterogeneous Clusters

Ahmad raeisi, Mahdi Dolati, Sina Darabi, M. Sadegh Talebi, Patrick Eugster, Ahmad Khonsari

Towards Neural Kolmogorov Equations: Parallelizable SDE Learning with Neural PDEs

Arthur Bizzi, Olga Fink

Thermodynamic Deep Learning: Interpreting Gradient Descent as Energy Flow in a Learning Universe

Gokul Srinath Seetha Ram

Parameterized Anchor Representations via Adaptive Matrices (PARAM) for Relative-Representations

Oscar Thorsted Svendsen, Nikolaj Holst Jakobsen, Fabian Mager, Hiba Nassar

The Brittleness of Priors: An Empirical Case for Adaptive Neural Architectures

Dawud Hage

15:15 – 17:15 Diversity in AI (Program)

17:15 – 18:00 Mingling session

18:00: Trip to Sommarøy

Wednesday, Jan. 7th:

08:30-09:00 Registration & Coffee

09:00-09:45 Keynote Talk: Devis Tuia

09:45-10:20 Coffee break

10:20-11:40 Oral session 3 (4 x 15 min talks + 5 min questions per talk)

10:20 – 10:40: AI-Enabled Vessels Segmentation Model for Real-Time Laparoscopic Ultrasound Imaging

Ignas Kupcikevicius, Luca Boretto, Inger A. Grunbeck, Rahul Prasanna Kumar, VARATHARAJAN NAINAMALAI, Mehdi Sadat Akhavi, Bjørn Edwin, Ole Jakob Elle

10:40 – 11:00:Incorporating the Cycle Inductive Bias in Masked Autoencoders

Stuart Gallina Ottersen, Kerstin Bach

11:00 – 11:20: Kolmogorov–Arnold Networks for Cross-Domain Time-Series Modeling in Health and Activity Monitoring

Hamza Haruna Mohammed, Gabriel Kiss, Frank Lindseth

11:20 – 11:40: Spatio-Temporal Landmark Detection via Selective Fine-Tuning of Echocardiography Foundation Models

Preetraj Bhoodoo, Sarina Thomas, Elisabeth Wetzer, Anne Schistad Solberg, Guy Ben-Yosef

11:40-11:45 Group Photo

11:45-12:45 Lunch

12:45-13:30 Keynote Talk: Ira Assent

13:30-15:00 Poster session 2

AI-Enabled Vessels Segmentation Model for Real-Time Laparoscopic Ultrasound Imaging

Ignas Kupcikevicius, Luca Boretto, Inger A. Grunbeck, Rahul Prasanna Kumar, VARATHARAJAN NAINAMALAI, Mehdi Sadat Akhavi, Bjørn Edwin, Ole Jakob Elle

Incorporating the Cycle Inductive Bias in Masked Autoencoders

Stuart Gallina Ottersen, Kerstin Bach

Kolmogorov–Arnold Networks for Cross-Domain Time-Series Modeling in Health and Activity Monitoring

Hamza Haruna Mohammed, Gabriel Kiss, Frank Lindseth

Spatio-Temporal Landmark Detection via Selective Fine-Tuning of Echocardiography Foundation Models

Preetraj Bhoodoo, Sarina Thomas, Elisabeth Wetzer, Anne Schistad Solberg, Guy Ben-Yosef

How PARTs assemble into wholes: Learning the relative composition of images

Melika Ayoughi, Samira Abnar, Chen Huang, Christopher Michael Sandino, Sayeri Lala, Eeshan Gunesh Dhekane, Dan Busbridge, Shuangfei Zhai, Vimal Thilak, Joshua M. Susskind, Pascal Mettes, Paul Groth, Hanlin Goh

Using Ensemble Diffusion to Estimate Uncertainty for End-to-End Autonomous Driving

Florian Wintel, Sigmund Hennum Høeg, Gabriel Kiss, Frank Lindseth

SimGroupAttn: Similarity-Guided Group Attention for Vision Transformer to Incorporate Population Information in Plant Disease Detection

Wangyang Wu, Ribana Roscher, Niklas Tötsch

MTVNet: Multi-Contextual Transformers for Volumes – Network for Super-Resolution with Long-Range Interactions

August Leander Høeg, Sophia W. Bardenfleth, Hans Martin Kjer, Tim B. Dyrby, Vedrana Andersen Dahl, Anders Dahl

Structured Covariance Modeling Using Learned Mixture-of-Bases for Uncertainty in 3D Segmentation

Peter J.T. Kampen, Andreas With Aspe, Kristine Aavild Juhl, Anders Nymark Christensen, Morten Rieger Hannemose, Anders Dahl, Rasmus Reinhold Paulsen, Josefine Vilsbøll Sundgaard

Preserving Ordinality in Diabetic Retinopathy Grading through a Distribution-Based Loss Function

Lena Stelter, Valentina Corbetta, Soufyan Lakbir, Regina Beets-Tan, Ricardo P. M. Cruz, Jaime S Cardoso, Wilson Silva

Towards clinical application of liver, vessel, and tumor segmentation using partially labeled data

Eirik Agnalt Østmo, Keyur Radiya, Kristoffer Knutsen Wickstrøm, Michael Kampffmeyer, Karl Øyvind Mikalsen, Robert Jenssen

Towards Agnostic and Holistic Universal Image Segmentation with Bit Diffusion

Jakob Lønborg Christensen, Morten Rieger Hannemose, Anders Dahl, Vedrana Andersen Dahl

Comparing Foundation Models for Medical Images: A Study on Limited Data and Generalization

Ingrid Utseth, Amund Hansen Vedal, Sarina Thomas, Line Eikvil

EEG Guided Token Selection in VQ for Visual Brain Decoding

Abhishek Rathore, PushapDeep Singh, Arnav Bhavsar

Posters from extended abstracts:

Reducing Administrative Burden in Clinics: Utilizing OCR and LLM Technology for Seamless External Document Handling

Bahadır Eryılmaz

CONDITIONAL DIFFUSION INPAINTING FOR SKETCH-TO-FACE SYNTHESIS

Sanhita Pathak, Vinay Kaushik, Brejesh Lall

Hyperbolic Representation Learning for Spatial Biology: Evaluating Cell Type Hierarchies in Breast Cancer Imaging Data

Youssef Wally, Johan Mylius-Kroken, Michael Kampffmeyer, Rezvan Ehsani, Vladan Milosevic, Elisabeth Wetzer

Reconsidering Spatial Alignment for Longitudinal Breast Cancer Risk Prediction

Solveig Thrun, Stine Hansen, Zijun Sun, Nele Blum, Suaiba Amina Salahuddin, XIN WANG, Kristoffer Knutsen Wickstrøm, Elisabeth Wetzer, Robert Jenssen, Maik Stille, Michael Kampffmeyer

Lighting Enhancement and Skin Lesion Analysis in Macroscopic Images using Genetic Algorithms and Deep Neural Networks

Vanesa Gómez-Martínez, Cristina Soguero-Ruiz

Charting Cellular Networks in the Tumor Microenvironment: Graph Visualizations in Highly-Multiplexed Breast Cancer Tissue

Lara Elvevåg, Youssef Wally, Benjamin Ricaud, Vladan Milosevic, Elisabeth Wetzer

Physics-Based X-ray CT Simulation for Synthetic Data Generation and Deep Learning Segmentation of Energy Materials

Nadia Mariana Leal Reyes, Salvatore De Angelis, Estrid Buhl Naver, Luise Theil Kuhn, Peter Stanley Jørgensen

Autoencoder Spectral Unmixing for Single-Cell Raman Analysis

Emil Alstrup Jensen, Lasse Ebdrup Pedersen, Anders Kristensen, Line H Clemmensen

Physics-Informed Deep Learning for Fast Cerebral Perfusion Assessment in Stroke Digital Twins

Sebastiaan Broos, Thijs P. Kuipers, Henk Marquering

DIMAFv2: Interpretable Multimodal Disentangled Representations for Breast Cancer Survival Prediction

Aniek Eijpe, Soufyan Lakbir, Melis Erdal Cesur, Sara P. Oliveira, Sanne Abeln, Wilson Silva

Comparison of Neural Networks and Gradient Boosting Models on Ordinal Age Class Prediction using Mouse Trajectories

Tobias Wistuba, Lisa Bondo Andersen, Ailin Liu, Felix Henninger, Frauke Kreuter, Sonja Greven

Impact of algorithm choice when using off-the-shelf AI segmentation methods in large-scale medical analyses

Emelie Bäcklin, Eva Breznik

Towards Multimodal Deep Learning for Predicting Survival of Brain Metastatic Cancer

Inês N. Carvalho

InV3st: Open-Vocabulary Object Detection and Instance Segmentation in 3D Crime Scenes

Michael Greza, Florian Eichinger, Yi Wang, Benjamin Busam

15:00-16:40 Oral session 4 (5 x 15 minute talks + 5 min questions per talk)

15:00 - 15:20: How PARTs assemble into wholes: Learning the relative composition of images

15:20 - 15:40: Using Ensemble Diffusion to Estimate Uncertainty for End-to-End Autonomous Driving

Florian Wintel, Sigmund Hennum Høeg, Gabriel Kiss, Frank Lindseth

15:40 - 16:00: SimGroupAttn: Similarity-Guided Group Attention for Vision Transformer to Incorporate Population Information in Plant Disease Detection

Wangyang Wu, Ribana Roscher, Niklas Tötsch

16:00 - 16:20: MTVNet: Multi-Contextual Transformers for Volumes – Network for Super-Resolution with Long-Range Interactions

August Leander Høeg, Sophia W. Bardenfleth, Hans Martin Kjer, Tim B. Dyrby, Vedrana Andersen Dahl, Anders Dahl

16:20 - 16:40 Structured Covariance Modeling Using Learned Mixture-of-Bases for Uncertainty in 3D Segmentation

Peter J.T. Kampen, Andreas With Aspe, Kristine Aavild Juhl, Anders Nymark Christensen, Morten Rieger Hannemose, Anders Dahl, Rasmus Reinhold Paulsen, Josefine Vilsbøll Sundgaard

19:00- Conference dinner at Scandic Ishavshotel (Google Maps)

Thursday, Jan. 8th:

08:30-09:00 Registration & Coffee

09:00-09:45 Keynote Talk: Shaheen Syed

09:45-10:10 Coffee break

10:10-10:50 Oral session 5 (4 x 15 min talks + 5 min questions per talk)

HetGSMOTE: Oversampling for Heterogeneous Graphs

Adhilsha Ansad, Deependra Singh, Rucha Bhalchandra Joshi, Subhankar Mishra

Design and Evaluation of a Geometric Algebra-Based Graph Neural Network for Molecular Property Prediction

Kasper Helverskov Petersen, Mikkel N. Schmidt

10:50 – 11:50 Lunch

11:50 – 13:20 Poster session 3

HetGSMOTE: Oversampling for Heterogeneous Graphs

Adhilsha Ansad, Deependra Singh, Rucha Bhalchandra Joshi, Subhankar Mishra

https://openreview.net/forum?id=rLzas2xQGs

Design and Evaluation of a Geometric Algebra-Based Graph Neural Network for Molecular Property Prediction

Kasper Helverskov Petersen, Mikkel N. Schmidt

https://openreview.net/forum?id=aHHQByxsjB

Reducing Manual Workload in SAR-Based Oil Spill Detection Through Uncertainty-Aware Deep Learning

Dina Svendsen Solskinnsbakk, Sigurd Almli Hanssen, Harald Lykke Joakimsen, Vilde B. Gjærum, Elisabeth Wetzer, Kristoffer Knutsen Wickstrøm

https://openreview.net/forum?id=8wgwRsfTuH

Learning Normal Patterns in Musical Loops

Shayan Dadman, Bernt Arild Bremdal, Børre Bang, Rune Dalmo

https://openreview.net/forum?id=Pr22XVnMW1

Predicting Calving Events in Antarctica using Machine Learning

Jacob Alexander Hay, Hamzeh Issa, David Parkes, Daniele Fantin, Jan Wuite, Amber A Leeson, Malcolm McMillan

https://openreview.net/forum?id=N5Y1FoRfiY

Self-Supervised and Unsupervised Multispectral Anomaly Detection for Unknown Substance and Surface Defect Identification

Cansu Beyaz, Mohamed Farag, Peer Schütt, Tobias Hecking, Jonas Grzesiak, Christoph Geiß, Ribana Roscher

https://openreview.net/forum?id=xFMoxTu1Te

Reflective Agents for Knowledge Graph Traversal

Michal Chudoba

Predictive and Explanatory Uncertainties in Graph Neural Networks: A Case Study in Molecular Property Prediction

Marisa Wodrich, Aasa Feragen, Mikkel N. Schmidt

RAG in the Aerospace Domain: A Comprehensive Retrieval, Generation, and User Evaluation for NASA Documentation

Dominykas Petniunas, Gabriel Iturra-Bocaz, Petra Galuscakova

Wildfire Spread Scenarios: Increasing Sample Diversity of Segmentation Diffusion Models with Training-Free Methods

Sebastian Gerard, Josephine Sullivan

Towards Visual Re-Identification of Fish using Fine-Grained Classification for Electronic Monitoring in Fisheries

Mahagedara Waththe Samitha Nuwan Thilakarathna, Ercan Avsar, Martin Mathias Nielsen, Malte Pedersen

Posters from extended abstracts:

AI Must not be Fully Autonomous

Tosin Adewumi, Lama Alkhaled, Florent Imbert, Hui Han, Nudrat Habib, Karl Löwenmark

T-PhISH-Net: Temporally Consistent Underwater Image Enhancement via a Transformer-Based Extension of PhISH-Net

Bjørn Christian Weinbach

Enhancing Wind Power Forecasting with Adaptive Wind Speed Calibration (C-LSTM) and a Hybrid (LTC+XGBoost) Model

Merve Nur Akyer, Michael Nickel, Cagil Karakas

Towards Explainable Multimodal Land Cover Segmentation Using Swin Transformer

Islomjon Shukhratov, Mehak Khan, Reza Arghandeh

Enhancing Bitcoin Price Volatility Estimator Predictions: A Four-Step Methodological Approach Utilizing Elastic Net Regression

Georgia Zournatzidou, IOANNIS MALLIDIS, Dimitrios Farazakis, Christos Floros

Machine Learning Techniques for Matching Candidates’ Profiles with Job Advertisements

Aleksandra Davidova Stefanova, Tosin Adewumi

Augmenting Large Language Models with Knowledge Graphs for Domain-Specific Applications

Sushanta Mohapatra, Tosin Adewumi

AI-Driven Talent Matching Predicting Employee Retention Through Candidate Attribute Analysis

Yasir Imtiaz Shami, Tosin Adewumi

Research on deep learning-based water quality prediction and management for intelligent aquaculture systems

Ji-Yeon Kim, Ki-Hwan Kim, Young-Jin Kang, Seok Chan Jeong

Large Language Models for Low-Resource Languages: A Plan for Te Reo Māori

Luca Blaauw Fossen, Albert Bifet, Te Taka Keegan, Samia Touileb

Subsurface Insight: Spatio-Temporal Embeddings for Hydrogeological Time Series Analysis

Quach Van Dang, Lynh HOANG-Vy-Thuy, Tuan-Anh Tran

A diffusion based approach for Oil Spill Detection in SAR Images

Sigurd Almli Hanssen, Dina Svendsen Solskinnsbakk, Harald Lykke Joakimsen, Vilde B. Gjærum, Kristoffer Knutsen Wickstrøm, Elisabeth Wetzer

Super-Resolution of Sentinel-5P Data Using Deep Learning

Saad Ahmed Jamal

Environmental Determinants of Healthcare Demand: An Explainable ML Approach for Lisbon’s Air Quality-Health Nexus

Helder Relvas, Behrouz Nemati, Sina Ataee, Farzaneh Abedian Aval, Vânia Martins, Bárbara T. Silva, Diogo Lopes, Ana Isabel Miranda

Clustering Mouse Movement Behavior in Surveys Using ResNet Embeddings

Lisa Bondo Andersen, Tobias Wistuba, Felix Henninger, Ailin Liu, Sonja Greven, Frauke Kreuter

Muffin: Muffled Audio Encoding with Filter-Based Masking

Marcel A. Vélez Vásquez

13:20 – 14:00 Oral session 6 (2 x 15 min talks + 5 min questions per talk)

Reducing Manual Workload in SAR-Based Oil Spill Detection Through Uncertainty-Aware Deep Learning

Dina Svendsen Solskinnsbakk, Sigurd Almli Hanssen, Harald Lykke Joakimsen, Vilde B. Gjærum, Elisabeth Wetzer, Kristoffer Knutsen Wickstrøm

Learning Normal Patterns in Musical Loops

Shayan Dadman, Bernt Arild Bremdal, Børre Bang, Rune Dalmo

14:00-15:00 NORA panel discussion

15:00-16:45 Industry and AI (Program)

16:45-17:00 Closing

19:00-22:00 Meet the AI Industry at Storgata Camping

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