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Editors: Hyeongji Kim, Adín Ramírez Rivera, Benjamin Ricaud
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HetGSMOTE: Oversampling for Heterogeneous Graphs
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:1-14
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; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:15-26
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; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:27-38
Spatio-Temporal Landmark Detection via Selective Fine-Tuning of Echocardiography Foundation Models
Preetraj Bhoodoo, Sarina Thomas, Elisabeth Wetzer, Anne Schistad Solberg, Guy Ben-Yosef; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:39-48
Towards Agnostic and Holistic Universal Image Segmentation with Bit Diffusion
Jakob Lønborg Christensen, Morten Rieger Hannemose, Anders Dahl, Vedrana Andersen Dahl; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:49-56
Reflective Agents for Knowledge Graph Traversal
Michal Chudoba; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:57-71
CID: Measuring Feature Importance Through Counterfactual Distributions
Eddie Conti, Álvaro Parafita, Axel Brando; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:72-85
Learning Normal Patterns in Musical Loops
Shayan Dadman, Bernt Arild Bremdal, Børre Bang, Rune Dalmo; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:86-105
Unreliable Monte Carlo Dropout Uncertainty Estimation
Aslak Djupskås, Signe Riemer-Sørensen, Alexander Johannes Stasik; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:106-114
Wildfire Spread Scenarios: Increasing Sample Diversity of Segmentation Diffusion Models with Training-Free Methods
Sebastian Gerard, Josephine Sullivan; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:115-130
Predicting Calving Events in Antarctica using Machine Learning
Jacob Alexander Hay, Hamzeh Issa, Daniele Fantin, David Parkes, Jan Wuite, Amber A Leeson, Malcolm McMillan; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:131-143
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; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:144-159
On the Generalisation of Koopman Representations for Chaotic System Control
Kyriakos Hjikakou, Juan Cardenas-Cartagena, Matthia Sabatelli; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:160-178
Staying on the Manifold: Geometry-Aware Noise Injection
Albert Kjøller Jacobsen, Johanna Marie Gegenfurtner, Georgios Arvanitidis; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:179-190
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; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:191-200
Extremal Contours: Gradient-driven contours for compact visual attribution
Reza Karimzadeh, Albert Alonso, Frans Zdyb, Julius B. Kirkegaard, Bulat Ibragimov; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:201-210
Assessing the Fragility of SHAP-Based Model Explanations Using Counterfactuals
Cornelia C. Käsbohrer, Sebastian Mair, Lili Jiang; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:211-234
Counterfactual generation for Out-of-Distribution data
Nawid Keshtmand, Raul Santos-Rodriguez, Jonathan Lawry; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:235-246
Analyzing Fairness of Neural Network Prediction via Counterfactual Dataset Generation
Brian Hyeongseok Kim, Jacqueline Mitchell, Chao Wang; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:247-262
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; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:263-273
Improving Vision Model Robustness against Misclassification and Uncertainty Attacks via Underconfidence Adversarial Training
Josué Martı́nez-Martı́nez, John T Holodnak, Olivia Brown, Sheida Nabavi, Derek Aguiar, Allan Wollaber; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:274-286
Kolmogorov–Arnold Networks for Cross-Domain Time-Series Modeling in Health and Activity Monitoring
Hamza Haruna Mohammed, Gabriel Kiss, Frank Lindseth; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:287-306
Hybrid Concept-based Models: Using Concepts to Improve Neural Networks’ Accuracy
Tobias Aanderaa Opsahl; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:307-318
Incorporating the Cycle Inductive Bias in Masked Autoencoders
Stuart Gallina Ottersen, Kerstin Bach; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:319-327
Design and Evaluation of a Geometric Algebra-Based Graph Neural Network for Molecular Property Prediction
Kasper Helverskov Petersen, Mikkel N. Schmidt; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:328-344
RAG in the Aerospace Domain: A Comprehensive Retrieval, Generation, and User Evaluation for NASA Documentation
Dominykas Petniunas, Gabriel Iturra-Bocaz, Petra Galuscakova; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:345-357
EEG Guided Token Selection in VQ for Visual Brain Decoding
Abhishek Rathore, PushapDeep Singh, Arnav Bhavsar; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:358-363
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; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:364-374
Investigating the relationship between diversity and generalization in deep neural networks
Ruan P. Van der Spoel, Randle Rabe; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:375-387
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; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:388-414
Liver, vessel, and tumor segmentation from partially labeled CT and multi-label masked learning
Eirik Agnalt Østmo, Keyur Radiya, Kristoffer Knutsen Wickstrøm, Michael Kampffmeyer, Karl Øyvind Mikalsen, Robert Jenssen; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:415-427
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; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:428-438
Comparing Foundation Models for Medical Images: A Study on Limited Data and Generalization
Ingrid Utseth, Amund Hansen Vedal, Sarina Thomas, Line Eikvil; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:439-447
Explaining Latent Representations of Neural Networks with Archetypal Analysis
Anna Emilie Jennow Wedenborg, Teresa Dorszewski, Lars Kai Hansen, Kristoffer Knutsen Wickstrøm, Morten Mørup; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:448-468
Using Ensemble Diffusion to Estimate Uncertainty for End-to-End Autonomous Driving
Florian Wintel, Sigmund Hennum Høeg, Gabriel Kiss, Frank Lindseth; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:469-486
Predictive and Explanatory Uncertainties in Graph Neural Networks: A Case Study in Molecular Property Prediction
Marisa Wodrich, Aasa Feragen, Mikkel N. Schmidt; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:487-495
SimGroupAttn: Similarity-Guided Group Attention for Vision Transformer to Incorporate Population Information in Plant Disease Detection
Wangyang Wu, Ribana Roscher, Niklas Tötsch; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:496-507
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