Sigurd Løkse
Researcher
sigl@norceresearch.no
+47 56 10 78 59
Forskningsparken Tromsø, Sykehusvn 23, 9019 Tromsø
Division
Energy & Technology
Research themes
Computer Vision
Artificial Intelligence and Machine Learning
Research Groups
More information about Sigurd
Projects
Publications
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Academic articleThe Conditional Cauchy-Schwarz Divergence With Applications to Time-Series Data and Sequential Decision Making– IEEE Transactions on Pattern Analysis and Machine Intelligence 2025
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Academic articleCauchy-Schwarz Divergence Information Bottleneck for Regression– International Conference on Learning Representations 2024
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Academic articleLeveraging tensor kernels to reduce objective function mismatch in deep clustering– Pattern Recognition 2024
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Academic articleRELAX: Representation Learning Explainability– International Journal of Computer Vision 2023
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Academic articleOn the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering– Computer Vision and Pattern Recognition 2023
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Academic articleHubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-shot Learning with Hyperspherical Embeddings– Computer Vision and Pattern Recognition 2023
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Academic articleAnalysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy– Entropy 2023
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Conference lectureDeep Clustering with the Cauchy-Schwarz Divergence– The AAAI-22 Workshop on Information Theory for Deep Learning (IT4DL) 2022
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Academic articleThe Kernelized Taylor Diagram– Communications in Computer and Information Science (CCIS) 2022
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Conference lectureThe Kernelized Taylor Diagram– NAIS 2022 Symposium 2022
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Academic articleReservoir Computing Approaches for Representation and Classification of Multivariate Time Series– IEEE Transactions on Neural Networks and Learning Systems 2021
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Academic articleReconsidering Representation Alignment for Multi-View Clustering– Computer Vision and Pattern Recognition 2021
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Conference lectureTowards Explainable Representation Learning– Norsk Forening for Bildebehandling og Maskinlæring 2021 2021
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Academic articleDeep divergence-based approach to clustering– Neural Networks 2019
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Academic chapterBidirectional deep-readout echo state networks– 2018
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Academic articleThe deep kernelized autoencoder– Applied Soft Computing 2018
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Academic articleRanking Using Transition Probabilities Learned from Multi-Attribute Data– Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing 2018
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Academic chapterDeep divergence-based clustering– 2017
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Academic articleTraining Echo State Networks with Regularization Through Dimensionality Reduction– Cognitive Computation 2017
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Academic articleSpectral clustering using PCKID ? A probabilistic cluster kernel for incomplete data– Lecture Notes in Computer Science (LNCS) 2017
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Academic articleRobust clustering using a kNN mode seeking ensemble– Pattern Recognition 2017
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Academic articleDeep kernelized autoencoders– Lecture Notes in Computer Science (LNCS) 2017
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Conference lectureRobust Non-Parametric Mode Clustering– NIPS workshop on Adaptive and Scalable Nonparametric Methods in Machine Learning 2016
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Academic chapterConsensus Clustering Using kNN Mode Seeking– 2015
