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ORCID7th NLDL 2024: Tromsø, Norway
- Tetiana Lutchyn, Adín Ramírez Rivera, Benjamin Ricaud:
Northern Lights Deep Learning Conference, NLDL 2024, 9-11 January 2024, UiT The Arctic University, Tromsø, Norway. Proceedings of Machine Learning Research 233, PMLR 2024 - Antonios Alexos, Pierre Baldi:
FastStitch: Speech editing by hitch-hiking a pre-trained FastSpeech2 model. 1-6 - Pierre Baldi:
Deep Learning Over-Parameterization: the Shallow Fallacy. 7-12 - Tessa Bauman, Sven Goluza, Bruno Gasperov, Zvonko Kostanjcar:
Deep Reinforcement Learning for Goal-Based Investing Under Regime-Switching. 13-19 - Marie Bø-Sande, Edvin Benjaminsen, Neel Kanwal, Saul Fuster, Helga Hardardottir, Ingrid Lundal, Emilius A. M. Janssen, Kjersti Engan:
A Dual Convolutional Neural Network Pipeline for Melanoma Diagnostics and Prognostics. 20-26 - Lydia Bryan-Smith, Nina Dethlefs:
Towards AI for approximating hydrodynamic simulations as a 2D segmentation task. 27-35 - Jeffrey Nicholas Clark
, Edward Alexander Small, Nawid Keshtmand, Michelle Wing Lam Wan, Elena Fillola Mayoral, Enrico Werner, Christopher P. Bourdeaux, Raúl Santos-Rodríguez:
TraCE: Trajectory Counterfactual Explanation Scores. 36-45 - Anton Debner, Maximilian Krahn, Vesa Hirvisalo:
Scheduling conditional task graphs with deep reinforcement learning. 46-52 - Phuong Dinh, Deddy Jobson, Takashi Sano, Hirotada Honda, Shugo Nakamura:
Understanding Neural ODE prediction decision using SHAP. 53-58 - Jorge García-Torres, Øyvind Meinich-Bache, Siren Irene Rettedal, Amalie Kibsgaard, Sara Brunner, Kjersti Engan:
Comparative Analysis of Binary and Multiclass Activity Recognition in High-Quality Newborn Resuscitation Videos. 59-66 - Laurits Fromberg, Troels Nielsen, Flavia Dalia Frumosu, Line H. Clemmensen:
Beyond Accuracy: Fairness, Scalability, and Uncertainty Considerations in Facial Emotion Recognition. 67-74 - Carina Geldhauser, Hermann Diebel-Fischer:
Is diverse and inclusive AI trapped in the gap between reality and algorithmizability? 75-80 - Simon Hallösta, Mats Ingemar Pettersson, Mattias Dahl:
Effects of Foreground Augmentations in Synthetic Training Data on the Use of UAVs for Weed Detection. 81-88 - Alouette van Hove, Kristoffer Aalstad, Norbert Pirk:
Guiding drones by information gain. 89-96 - Are C. Jensen:
Beyond output-mask comparison: A self-supervised inspired object scoring system for building change detection. 97-103 - Jonas Vestergaard Jensen, Mikkel Jordahn, Michael Riis Andersen:
Neural machine translation for automated feedback on children's early-stage writing. 104-112 - Pål Vegard Johnsen, Filippo Remonato:
SafetyCage: A misclassification detector for feed-forward neural networks. 113-119 - Nawid Keshtmand, Raúl Santos-Rodríguez, Jonathan Lawry:
Typicality-based point OOD detection with contrastive learning. 120-129 - Simon Martinus Koop, Mark A. Peletier, Jacobus Willem Portegies, Vlado Menkovski:
Neural Langevin Dynamics: Towards Interpretable Neural Stochastic Differential Equations. 130-137 - Sebastian Nørgaard Llambias, Mads Nielsen, Mostafa Mehdipour-Ghazi:
Heterogeneous Learning for Brain Lesion Segmentation, Detection, and Classification. 138-144 - Jørgen Aarmo Lund, Karl Øyvind Mikalsen, Per Joel Burman, Ashenafi Zebene Woldaregay, Robert Jenssen:
Instruction-guided deidentification with synthetic test cases for Norwegian clinical text. 145-152 - Pieter Meiresone, David Van Hamme, Wilfried Philips:
Loop closure with a low power millimeter wave radar sensor using an autoencoder. 153-157 - Jon Middleton, Marko Bauer, Kaining Sheng, Jacob Johansen, Mathias Perslev, Silvia Ingala, Mads Nielsen, Akshay Pai:
Local Gamma Augmentation for Ischemic Stroke Lesion Segmentation on MRI. 158-164 - Aritra Mukhopadhyay, Adhilsha A, Subhankar Mishra:
Large Neural Networks at a Fraction. 165-173 - Asbjørn Munk, Mads Nielsen:
MDD-UNet: Domain Adaptation for Medical Image Segmentation with Theoretical Guarantees, a Proof of Concept. 174-180 - Beatrix Miranda Ginn Nielsen, Lars Kai Hansen:
Hubness Reduction Improves Sentence-BERT Semantic Spaces. 181-204 - Alberto Pepe, Sven Buchholz, Joan Lasenby:
Clifford Group Equivariant Neural Network Layers for Protein Structure Prediction. 205-211 - Gustav Grund Pihlgren, Fredrik Sandin, Marcus Liwicki:
Deep Perceptual Similarity is Adaptable to Ambiguous Contexts. 212-219 - Sanaullah:
A Hybrid Spiking-Convolutional Neural Network Approach for Advancing Machine Learning Models. 220-227 - Martijn Vermeer, Jacob Alexander Hay, David Völgyes, Zsófia Koma, Johannes Breidenbach, Daniele Fantin:
Lidar-based Norwegian tree species detection using deep learning. 228-234 - John Isak Fjellvang Villanger, Troels Arnfred Bojesen:
An Inductive Bias for Emergent Communication in a Continuous Setting. 235-243 - Edvin Listo Zec, Johan Östman, Olof Mogren, Daniel Gillblad:
Efficient Node Selection in Private Personalized Decentralized Learning. 244-250
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