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ORCID8th NLDL 2025: Tromsø, Norway
- Tetiana Lutchyn, Adín Ramírez Rivera, Benjamin Ricaud:
Northern Lights Deep Learning Conference, The Arctic University, Tromsø, Norway, 7-9 January 2025. Proceedings of Machine Learning Research 265, PMLR 2025 - Gabriel Y. Arteaga, Thomas B. Schön, Nicolas Pielawski:
Hallucination Detection in LLMs: Fast and Memory-Efficient Finetuned Models. 1-15 - Thea Brüsch, Kristoffer Knutsen Wickstrøm, Mikkel N. Schmidt, Tommy Sonne Alstrøm, Robert Jenssen:
FreqRISE: Explaining time series using frequency masking. 16-31 - Anton Debner, Vesa Hirvisalo:
Towards concurrent real-time audio-aware agents with deep reinforcement learning. 32-40 - Teresa Dorszewski, Lenka Tetková, Lorenz Linhardt, Lars Kai Hansen:
Connecting Concept Convexity and Human-Machine Alignment in Deep Neural Networks. 41-50 - Simen Eide, Arnoldo Frigessi:
BoRA: Bayesian Hierarchical Low-Rank Adaption for Multi-task Large Language Models. 51-57 - Philip Enevoldsen, Christian Gundersen, Nico Lang, Serge J. Belongie, Christian Igel:
Familiarity-Based Open-Set Recognition Under Adversarial Attacks. 58-65 - Jeremias Lino Ferrao, Rafael F. Cunha:
World Model Agents with Change-Based Intrinsic Motivation. 66-74 - Andreas Abildtrup Hansen, Paraskevas Pegios, Anna Calissano, Aasa Feragen:
Graph Counterfactual Explainable AI via Latent Space Traversal. 75-84 - Paul Häusner, Aleix Nieto Juscafresa, Jens Sjölund:
Learning incomplete factorization preconditioners for GMRES. 85-99 - Meadhbh Healy, Thomas Martini Jørgensen:
Enhancing Fault Detection in Optical Networks with Conditional Denoising Diffusion Probabilistic Models. 100-109 - Dhruv Jain, Tsiry Mayet, Romain Hérault, Romain Modzelewski:
One-Class SVM-guided Negative Sampling for Enhanced Contrastive Learning. 110-119 - Patrick Møller Jensen, Udaranga Wickramasinghe, Anders B. Dahl, Pascal Fua, Vedrana Andersen Dahl:
Deep Active Latent Surfaces for Medical Geometries. 120-132 - Pål Vegard Johnsen, Filippo Remonato, Shawn Benedict, Albert Ndur-Osei:
SPARDACUS SafetyCage: A new misclassification detector. 133-140 - Matthijs van der Lende, Matthia Sabatelli, Juan Cardenas-Cartagena:
Interpretable Function Approximation with Gaussian Processes in Value-Based Model-Free Reinforcement Learning. 141-154 - Julia Machnio, Mads Nielsen, Mostafa Mehdipour-Ghazi:
Deep Learning for Localization of White Matter Lesions in Neurological Diseases. 155-167 - Vincent Menden, Yahya Saleh, Armin Iske:
Bounds on the Generalization Error in Active Learning. 168-175 - Ibtihal El Mimouni, Konstantin Avrachenkov:
Deep Q-Learning with Whittle Index for Contextual Restless Bandits: Application to Email Recommender Systems. 176-183 - Bjørn Leth Møller, Sepideh Amiri, Christian Igel, Kristoffer Knutsen Wickstrøm, Robert Jenssen, Matthias Keicher, Mohammad Farid Azampour, Nassir Navab, Bulat Ibragimov:
NEMt: Fast Targeted Explanations for Medical Image Models via Neural Explanation Masks. 184-192 - Aritra Mukhopadhyay, Rucha Bhalchandra Joshi, Nidhi Tiwari, Subhankar Mishra:
Transformers at a fraction. 193-203 - Agney K. Rajeev, Joel Joseph K. B, Subhankar Mishra:
Predicting Oligomeric states of Fluorescent Proteins using Mamba. 204-212 - Joze M. Rozanec, Roy Krumpak, Martin Molan, Andrea Bartolini:
Learning anomalies from graph: predicting compute node failures on HPC clusters. 213-219 - Raghavendra Selvan, Bob Pepin, Christian Igel, Gabrielle Samuel, Erik B. Dam:
PePR: Performance Per Resource Unit as a Metric to Promote Small-scale Deep Learning. 220-229 - Poulami Sinhamahapatra, Shirsha Bose, Karsten Roscher, Stephan Günnemann:
Zero-Shot Open-Vocabulary OOD Object Detection and Grounding using Vision Language Models. 230-238 - Jon Sporring, Peidi Xu, Jiahao Lu, François Bernard Lauze, Sune Darkner:
Locally orderless networks. 239-244 - Lars Uebbing, Harald L. Joakimsen, Luigi Tommaso Luppino, Iver Martinsen, Andrew McDonald, Kristoffer Knutsen Wickstrøm, Sébastien Lefèvre, Arnt-Børre Salberg, Scott Hosking, Robert Jenssen:
Investigating the Impact of Feature Reduction for Deep Learning-based Seasonal Sea Ice Forecasting. 245-254 - Steven Wallace, Aiden Durrant, William David Harcourt, Richard Hann, Georgios Leontidis:
Exploring Segment Anything Foundation Models for Out of Domain Crevasse Drone Image Segmentation. 255-268 - Moritz Wohlstein, Ulf Brefeld:
Toward Learning Distributions of Distributions. 269-275
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last updated on 2025-11-08 00:49 CET by the dblp team
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