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Volume 307: Northern Lights Deep Learning Conference, 6-8 January 2026, UiT The Arctic University, Tromsø, Norway
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Editors: Hyeongji Kim, Adín Ramírez Rivera, Benjamin Ricaud
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
; 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
; 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
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:39-48
Towards Agnostic and Holistic Universal Image Segmentation with Bit Diffusion
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:49-56
Reflective Agents for Knowledge Graph Traversal
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:57-71
CID: Measuring Feature Importance Through Counterfactual Distributions
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:72-85
Learning Normal Patterns in Musical Loops
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:86-105
Unreliable Monte Carlo Dropout Uncertainty Estimation
; 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
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:115-130
Predicting Calving Events in Antarctica using Machine Learning
; 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
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:144-159
On the Generalisation of Koopman Representations for Chaotic System Control
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:160-178
Staying on the Manifold: Geometry-Aware Noise Injection
; 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
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:191-200
Extremal Contours: Gradient-driven contours for compact visual attribution
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:201-210
Assessing Explanation Fragility of SHAP using Counterfactuals
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:211-234
Counterfactual generation for Out-of-Distribution data
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:235-246
Analyzing Fairness of Neural Network Prediction via Counterfactual Dataset Generation
; 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
; 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
; 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
; 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
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:307-318
Incorporating the Cycle Inductive Bias in Masked Autoencoders
; 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
; 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
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:345-357
EEG Guided Token Selection in VQ for Visual Brain Decoding
; 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
; 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
; 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
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:388-414
Towards clinical application of liver, vessel, and tumor segmentation using partially labeled data
; 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
; 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
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:439-447
Explaining Latent Representations of Neural Networks with Archetypal Analysis
; 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
; 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
; 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
; Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:496-507
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