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ORCIDLars Kai Hansen
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- affiliation: Technical University of Denmark, Department of Applied Mathematics and Computer Science
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2020 – today
- 2024
[j70]Germans Savcisens
, Tina Eliassi-Rad, Lars Kai Hansen, Laust Hvas Mortensen, Lau Lilleholt, Anna Rogers, Ingo Zettler, Sune Lehmann:
Using sequences of life-events to predict human lives. Nat. Comput. Sci. 4(1): 43-56 (2024)- [c133]Sarthak Yadav, Sergios Theodoridis, Lars Kai Hansen, Zheng-Hua Tan:
Masked Autoencoders with Multi-Window Local-Global Attention Are Better Audio Learners. ICLR 2024 - [c132]Beatrix Miranda Ginn Nielsen, Lars Kai Hansen:
Hubness Reduction Improves Sentence-BERT Semantic Spaces. NLDL 2024: 181-204 - [c131]Lenka Tetková, Teresa Karen Scheidt, Maria Mandrup Fogh, Ellen Marie Gaunby Jørgensen, Finn Årup Nielsen, Lars Kai Hansen:
Knowledge Graphs for Empirical Concept Retrieval. xAI (1) 2024: 160-183 - [i42]Lenka Tetková, Teresa Karen Scheidt, Maria Mandrup Fogh, Ellen Marie Gaunby Jørgensen, Finn Årup Nielsen, Lars Kai Hansen:
Knowledge graphs for empirical concept retrieval. CoRR abs/2404.07008 (2024) - [i41]Lenka Tetková, Erik Schou Dreier, Robin Malm, Lars Kai Hansen:
Challenges in explaining deep learning models for data with biological variation. CoRR abs/2406.09981 (2024) - [i40]Anders Gjølbye Madsen, Lina Skerath, William Theodor Lehn-Schiøler, Nicolas Langer, Lars Kai Hansen:
SPEED: Scalable Preprocessing of EEG Data for Self-Supervised Learning. CoRR abs/2408.08065 (2024) - [i39]Teresa Dorszewski, Lenka Tetková, Lars Kai Hansen:
Convexity-based Pruning of Speech Representation Models. CoRR abs/2408.11858 (2024) - [i38]Teresa Dorszewski, Lenka Tetková, Lorenz Linhardt, Lars Kai Hansen:
Connecting Concept Convexity and Human-Machine Alignment in Deep Neural Networks. CoRR abs/2409.06362 (2024) - [i37]Teresa Dorszewski, Albert Kjøller Jacobsen, Lenka Tetková, Lars Kai Hansen:
How Redundant Is the Transformer Stack in Speech Representation Models? CoRR abs/2409.16302 (2024) - [i36]Gustav Wagner Zakarias, Lars Kai Hansen, Zheng-Hua Tan:
BiSSL: Bilevel Optimization for Self-Supervised Pre-Training and Fine-Tuning. CoRR abs/2410.02387 (2024) - 2023
- [c130]Lenka Tetková, Lars Kai Hansen:
Robustness of Visual Explanations to Common Data Augmentation Methods. CVPR Workshops 2023: 3715-3720 - [c129]Anders Gjølbye Madsen, William Theodor Lehn-Schiøler, Áshildur Jónsdóttir, Bergdís Arnardóttir, Lars Kai Hansen:
Concept-Based Explainability for an EEG Transformer Model. MLSP 2023: 1-6 - [c128]Jonathan Foldager, Mikkel Jordahn, Lars Kai Hansen, Michael Riis Andersen:
On the role of model uncertainties in Bayesian optimisation. UAI 2023: 592-601 - [i35]Jonathan Foldager, Mikkel Jordahn, Lars Kai Hansen, Michael Riis Andersen:
On the role of Model Uncertainties in Bayesian Optimization. CoRR abs/2301.05983 (2023) - [i34]Lenka Tetková, Lars Kai Hansen:
Robustness of Visual Explanations to Common Data Augmentation. CoRR abs/2304.08984 (2023) - [i33]Lenka Tetková, Thea Brüsch, Teresa Karen Scheidt, Fabian Martin Mager, Rasmus Ørtoft Aagaard, Jonathan Foldager, Tommy Sonne Alstrøm, Lars Kai Hansen:
On convex conceptual regions in deep network representations. CoRR abs/2305.17154 (2023) - [i32]Sarthak Yadav, Sergios Theodoridis, Lars Kai Hansen, Zheng-Hua Tan:
Masked Autoencoders with Multi-Window Attention Are Better Audio Learners. CoRR abs/2306.00561 (2023) - [i31]Germans Savcisens, Tina Eliassi-Rad, Lars Kai Hansen, Laust Hvas Mortensen, Lau Lilleholt, Anna Rogers, Ingo Zettler, Sune Lehmann:
Using Sequences of Life-events to Predict Human Lives. CoRR abs/2306.03009 (2023) - [i30]Anders Gjølbye Madsen, William Theodor Lehn-Schiøler, Áshildur Jónsdóttir, Bergdís Arnardóttir, Lars Kai Hansen:
Concept-based explainability for an EEG transformer model. CoRR abs/2307.12745 (2023) - [i29]Beatrix M. G. Nielsen, Lars Kai Hansen:
Hubness Reduction Improves Sentence-BERT Semantic Spaces. CoRR abs/2311.18364 (2023) - 2022
- [j69]Nicolai Pedersen, Torsten Dau, Lars Kai Hansen, Jens Hjortkjær:
Modulation transfer functions for audiovisual speech. PLoS Comput. Biol. 18(7) (2022) - 2021
- [j68]Greta Tuckute, Sofie Therese Hansen, Troels Wesenberg Kjaer, Lars Kai Hansen:
Real-Time Decoding of Attentional States Using Closed-Loop EEG Neurofeedback. Neural Comput. 33(4): 967-1004 (2021) - [c127]Christoffer Riis, Damian Konrad Kowalczyk, Lars Kai Hansen:
On the Limits to Multi-modal Popularity Prediction on Instagram: A New Robust, Efficient and Explainable Baseline. ICAART (2) 2021: 1200-1209 - [c126]Cilie W. Feldager, Søren Hauberg, Lars Kai Hansen:
Spontaneous Symmetry Breaking in Data Visualization. ICANN (2) 2021: 435-446 - [i28]Petr Taborsky, Lars Kai Hansen:
Generalization by design: Shortcuts to Generalization in Deep Learning. CoRR abs/2107.02253 (2021) - [i27]Raluca Alexandra Fetic, Mikkel Jordahn, Lucas Chaves Lima, Rasmus Arpe Fogh Egebæk, Martin Carsten Nielsen, Benjamin Biering, Lars Kai Hansen:
Topic Model Robustness to Automatic Speech Recognition Errors in Podcast Transcripts. CoRR abs/2109.12306 (2021) - 2020
- [j67]Jia Qian, Lars Kai Hansen, Xenofon Fafoutis, Prayag Tiwari, Hari Mohan Pandey:
Robustness analytics to data heterogeneity in edge computing. Comput. Commun. 164: 229-239 (2020) - [c125]Damian Konrad Kowalczyk, Lars Kai Hansen:
The Complexity of Social Media Response: Statistical Evidence for One-dimensional Engagement Signal in Twitter. ICAART (2) 2020: 918-925 - [i26]Jia Qian, Xenofon Fafoutis, Lars Kai Hansen:
Towards Federated Learning: Robustness Analytics to Data Heterogeneity. CoRR abs/2002.05038 (2020) - [i25]Laura Rieger, Lars Kai Hansen:
IROF: a low resource evaluation metric for explanation methods. CoRR abs/2003.08747 (2020) - [i24]Christoffer Riis, Damian Konrad Kowalczyk, Lars Kai Hansen:
On the Limits to Multi-Modal Popularity Prediction on Instagram - A New Robust, Efficient and Explainable Baseline. CoRR abs/2004.12482 (2020) - [i23]Jeppe Nørregaard, Lars Kai Hansen:
Probabilistic Decoupling of Labels in Classification. CoRR abs/2006.09046 (2020) - [i22]Laura Rieger, Rasmus M. Th. Høegh, Lars Kai Hansen:
Client Adaptation improves Federated Learning with Simulated Non-IID Clients. CoRR abs/2007.04806 (2020) - [i21]Laura Rieger, Lars Kai Hansen:
A simple defense against adversarial attacks on heatmap explanations. CoRR abs/2007.06381 (2020) - [i20]Jia Qian, Lars Kai Hansen:
What can we learn from gradients? CoRR abs/2010.15718 (2020)
2010 – 2019
- 2019
- [j66]Sofie Therese Hansen, Apit Hemakom, Mads Gylling Safeldt, Lærke Karen Krohne, Kristoffer Hougaard Madsen, Hartwig R. Siebner, Danilo P. Mandic, Lars Kai Hansen:
Unmixing Oscillatory Brain Activity by EEG Source Localization and Empirical Mode Decomposition. Comput. Intell. Neurosci. 2019: 5618303:1-5618303:15 (2019) - [j65]Greta Tuckute, Sofie Therese Hansen, Nicolai Pedersen, Dea Steenstrup, Lars Kai Hansen:
Single-Trial Decoding of Scalp EEG under Natural Conditions. Comput. Intell. Neurosci. 2019: 9210785:1-9210785:11 (2019) - [c124]Jia Qian, Sarada Prasad Gochhayat, Lars Kai Hansen:
Distributed Active Learning Strategies on Edge Computing. CSCloud/EdgeCom 2019: 221-226 - [c123]Niels Bruun Ipsen, Lars Kai Hansen:
Phase transition in PCA with missing data: Reduced signal-to-noise ratio, not sample size! ICML 2019: 2951-2960 - [c122]Finn Årup Nielsen, Lars Kai Hansen:
Combining embedding methods for a word intrusion task. KONVENS 2019 - [p3]Lars Kai Hansen, Laura Rieger:
Interpretability in Intelligent Systems - A New Concept? Explainable AI 2019: 41-49 - [e1]Wojciech Samek, Grégoire Montavon, Andrea Vedaldi, Lars Kai Hansen, Klaus-Robert Müller:
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning. Lecture Notes in Computer Science 11700, Springer 2019, ISBN 978-3-030-28953-9 [contents] - [i19]Laura Rieger, Lars Kai Hansen:
Aggregating explainability methods for neural networks stabilizes explanations. CoRR abs/1903.00519 (2019) - [i18]Niels Bruun Ipsen, Lars Kai Hansen:
Phase transition in PCA with missing data: Reduced signal-to-noise ratio, not sample size! CoRR abs/1905.00709 (2019) - [i17]Jeppe Nørregaard, Lars Kai Hansen:
Probabilistic Decoupling of Labels in Classification. CoRR abs/1905.12403 (2019) - [i16]Jia Qian, Sayantan Sengupta, Lars Kai Hansen:
Active Learning Solution on Distributed Edge Computing. CoRR abs/1906.10718 (2019) - [i15]Damian Konrad Kowalczyk, Lars Kai Hansen:
The Complexity of Social Media Response: Statistical Evidence For One-Dimensional Engagement Signal in Twitter. CoRR abs/1910.02807 (2019) - 2018
- [j64]Rasmus Troelsgård, Lars Kai Hansen:
Sequence Classification Using Third-Order Moments. Neural Comput. 30(1) (2018) - [j63]Tülay Adali, H. Joel Trussell, Lars Kai Hansen, Vince D. Calhoun:
The Dangers of Following Trends in Research: Sparsity and Other Examples of Hammers in Search of Nails. Proc. IEEE 106(6): 1014-1018 (2018) - [c121]Michael Riis Andersen, Ole Winther, Lars Kai Hansen, Russell A. Poldrack, Oluwasanmi Koyejo:
Bayesian Structure Learning for Dynamic Brain Connectivity. AISTATS 2018: 1436-1446 - [c120]Finn Årup Nielsen, Lars Kai Hansen:
Inferring Visual Semantic Similarity with Deep Learning and Wikidata: Introducing imagesim-353*. DL4KGS@ESWC 2018: 56-61 - [c119]Andreas Muff Munk, Kristoffer Vinther Olesen, Sirin Wilhelmsen Gangstad, Lars Kai Hansen:
Semi-Supervised Sleep-Stage Scoring Based on Single Channel EEG. ICASSP 2018: 2551-2555 - [c118]Søren Føns Vind Nielsen, Yuri Levin-Schwartz, Diego Vidaurre, Tülay Adali, Vince D. Calhoun, Kristoffer Hougaard Madsen, Lars Kai Hansen, Morten Mørup:
Evaluating Models of Dynamic Functional Connectivity Using Predictive Classification Accuracy. ICASSP 2018: 2566-2570 - [c117]Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg:
Latent Space Oddity: on the Curvature of Deep Generative Models. ICLR (Poster) 2018 - [c116]Teresa Anna Steiner, David Enslev Nyrnberg, Lars Kai Hansen:
A Differential Privacy Workflow for Inference of Parameters in the Rasch Model. MIDAS/PAP@PKDD/ECML 2018: 113-124 - 2017
- [j62]Michael Riis Andersen, Aki Vehtari, Ole Winther, Lars Kai Hansen:
Bayesian Inference for Spatio-temporal Spike-and-Slab Priors. J. Mach. Learn. Res. 18: 139:1-139:58 (2017) - [j61]Sofie Therese Hansen, Lars Kai Hansen:
Spatio-temporal reconstruction of brain dynamics from EEG with a Markov prior. NeuroImage 148: 274-283 (2017) - [c115]Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg:
Maximum Likelihood Estimation of Riemannian Metrics from Euclidean Data. GSI 2017: 38-46 - [c114]Rasmus S. Andersen, Anders U. Eliasen, Nicolai Pedersen, Michael Riis Andersen, Sofie Therese Hansen, Lars Kai Hansen:
EEG source imaging assists decoding in a face recognition task. ICASSP 2017: 939-943 - [c113]Albert Vilamala, Kristoffer Hougaard Madsen, Lars Kai Hansen:
Deep convolutional neural networks for interpretable analysis of EEG sleep stage scoring. MLSP 2017: 1-6 - [c112]Albert Vilamala, Kristoffer Hougaard Madsen, Lars Kai Hansen:
Adaptive smoothing in fMRI data processing neural networks. PRNI 2017: 1-4 - [i14]Albert Vilamala, Kristoffer Hougaard Madsen, Lars Kai Hansen:
Adaptive Smoothing in fMRI Data Processing Neural Networks. CoRR abs/1710.00629 (2017) - [i13]Albert Vilamala, Kristoffer Hougaard Madsen, Lars Kai Hansen:
Deep Convolutional Neural Networks for Interpretable Analysis of EEG Sleep Stage Scoring. CoRR abs/1710.00633 (2017) - 2016
- [j60]Gitte Moos Knudsen, Peter S. Jensen, David Erritzoe, William F. C. Baaré, Anders Ettrup, Patrick M. Fisher, Nic Gillings, Hanne D. Hansen, Lars Kai Hansen, Steen Gregers Hasselbalch, Susanne Henningsson, Matthias M. Herth, Klaus K. Holst, Pernille Iversen, Lars Vedel Kessing, Julian Macoveanu, Kathrine Skak Madsen, Erik L. Mortensen, Finn Årup Nielsen, Olaf B. Paulson, Hartwig R. Siebner, Dea S. Stenbæk, Claus Svarer, Terry L. Jernigan, Stephen C. Strother, Vibe G. Frokjaer:
The Center for Integrated Molecular Brain Imaging (Cimbi) database. NeuroImage 124: 1213-1219 (2016) - [j59]Sofie Therese Hansen, Søren Hauberg, Lars Kai Hansen:
Data-driven forward model inference for EEG brain imaging. NeuroImage 139: 249-258 (2016) - [c111]Søren Hauberg, Oren Freifeld, Anders Boesen Lindbo Larsen, John W. Fisher III, Lars Kai Hansen:
Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation. AISTATS 2016: 342-350 - [c110]Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg:
A Locally Adaptive Normal Distribution. NIPS 2016: 4251-4259 - [i12]Andreas Trier Poulsen, Simon Kamronn, Jacek Dmochowski, Lucas C. Parra, Lars Kai Hansen:
Measuring engagement in a classroom: Synchronised neural recordings during a video presentation. CoRR abs/1604.03019 (2016) - [i11]Albert Vilamala, Kristoffer Hougaard Madsen, Lars Kai Hansen:
Towards end-to-end optimisation of functional image analysis pipelines. CoRR abs/1610.04079 (2016) - 2015
- [j58]Simon Kamronn, Andreas Trier Poulsen, Lars Kai Hansen:
Multiview Bayesian Correlated Component Analysis. Neural Comput. 27(10): 2207-2230 (2015) - [j57]Tülay Adali, Christian Jutten, Lars Kai Hansen:
Multimodal Data Fusion [Scanning the Issue]. Proc. IEEE 103(9): 1445-1448 (2015) - [c109]Sofie Therese Hansen, Lars Kai Hansen:
EEG source reconstruction performance as a function of skull conductance contrast. ICASSP 2015: 827-831 - [c108]Sofie Therese Hansen, Irene Winkler, Lars Kai Hansen, Klaus-Robert Müller, Sven Dähne:
Fusing Simultaneous EEG and fMRI Using Functional and Anatomical Information. PRNI 2015: 33-36 - [c107]Martin C. Axelsen, Nikolaj Bak, Lars Kai Hansen:
Testing Multimodal Integration Hypotheses with Application to Schizophrenia Data. PRNI 2015: 37-40 - [i10]Søren Hauberg, Oren Freifeld, Anders Boesen Lindbo Larsen, John W. Fisher III, Lars Kai Hansen:
Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation. CoRR abs/1510.02795 (2015) - 2014
- [j56]Jair Montoya-Martínez, Antonio Artés-Rodríguez, Massimiliano Pontil, Lars Kai Hansen:
A regularized matrix factorization approach to induce structured sparse-low-rank solutions in the EEG inverse problem. EURASIP J. Adv. Signal Process. 2014: 97 (2014) - [j55]Ivana Konvalinka, Markus Bauer, Carsten Stahlhut, Lars Kai Hansen, Andreas Roepstorff, Chris D. Frith:
Frontal alpha oscillations distinguish leaders from followers: Multivariate decoding of mutually interacting brains. NeuroImage 94: 79-88 (2014) - [j54]Kasper Winther Andersen, Kristoffer Hougaard Madsen, Hartwig Roman Siebner, Mikkel N. Schmidt, Morten Mørup, Lars Kai Hansen:
Non-parametric Bayesian graph models reveal community structure in resting state fMRI. NeuroImage 100: 301-315 (2014) - [j53]Toke Jansen Hansen, Trine Julie Abrahamsen, Lars Kai Hansen:
Denoising by semi-supervised kernel PCA preimaging. Pattern Recognit. Lett. 49: 114-120 (2014) - [c106]Lars Kai Hansen, Søren Holdt Jensen, Jan Larsen:
Preface. CIP 2014: 1 - [c105]Rasmus Bonnevie, Lars Kai Hansen:
Fast sampling from a Hidden Markov Model posterior for large data. MLSP 2014: 1-6 - [c104]Bjarne Ørum Fruergaard, Lars Kai Hansen:
Compact web browsing profiles for click-through rate prediction. MLSP 2014: 1-6 - [c103]Michael Riis Andersen, Ole Winther, Lars Kai Hansen:
Bayesian Inference for Structured Spike and Slab Priors. NIPS 2014: 1745-1753 - [c102]Sofie Therese Hansen, Lars Kai Hansen:
EEG source reconstruction using sparse basis function representations. PRNI 2014: 1-4 - [c101]Andreas Trier Poulsen, Simon Kamronn, Lucas C. Parra, Lars Kai Hansen:
Bayesian correlated component analysis for inference of joint EEG activation. PRNI 2014: 1-4 - [i9]Arkadiusz Stopczynski, Dazza Greenwood, Lars Kai Hansen, Alex Pentland:
Privacy for Personal Neuroinformatics. CoRR abs/1403.2745 (2014) - [i8]Rasmus Troelsgård, Bjørn Sand Jensen, Lars Kai Hansen:
A Topic Model Approach to Multi-Modal Similarity. CoRR abs/1405.6886 (2014) - 2013
- [j52]Radu Dragusin, Paula Petcu, Christina Lioma, Birger Larsen, Henrik Jørgensen, Ingemar J. Cox, Lars Kai Hansen, Peter Ingwersen, Ole Winther:
FindZebra: A search engine for rare diseases. Int. J. Medical Informatics 82(6): 528-538 (2013) - [j51]Trine Julie Abrahamsen, Lars Kai Hansen:
Variance inflation in high dimensional Support Vector Machines. Pattern Recognit. Lett. 34(16): 2173-2180 (2013) - [j50]Jerónimo Arenas-García, Kaare Brandt Petersen, Gustavo Camps-Valls, Lars Kai Hansen:
Kernel Multivariate Analysis Framework for Supervised Subspace Learning: A Tutorial on Linear and Kernel Multivariate Methods. IEEE Signal Process. Mag. 30(4): 16-29 (2013) - [c100]Lars Kai Hansen, Sofie Therese Hansen, Carsten Stahlhut:
Mobile real-time EEG imaging Bayesian inference with sparse, temporally smooth source priors. BCI 2013: 6-7 - [c99]Bjørn Sand Jensen, Rasmus Troelsgård, Jan Larsen, Lars Kai Hansen:
Towards a universal representation for audio information retrieval and analysis. ICASSP 2013: 3168-3172 - [c98]Camilla Birgitte Falk Jensen, Michael Kai Petersen, Jakob Eg Larsen, Arkadiusz Stopczynski, Carsten Stahlhut, Marieta Georgieva Ivanova, Tobias Andersen, Lars Kai Hansen:
Spatio temporal media components for neurofeedback. ICME Workshops 2013: 1-6 - [c97]Carsten Stahlhut, Hagai Thomas Attias, Kensuke Sekihara, David P. Wipf, Lars Kai Hansen, Srikantan S. Nagarajan:
A hierarchical Bayesian M/EEG imagingmethod correcting for incomplete spatio-temporal priors. ISBI 2013: 560-563 - [c96]Michael Riis Andersen, Sofie Therese Hansen, Lars Kai Hansen:
Learning the solution sparsity of an ill-posed linear inverse problem with the Variational Garrote. MLSP 2013: 1-6 - [c95]Sofie Therese Hansen, Carsten Stahlhut, Lars Kai Hansen:
Sparse Source EEG Imaging with the Variational Garrote. PRNI 2013: 106-109 - [c94]Sofie Therese Hansen, Carsten Stahlhut, Lars Kai Hansen:
Expansion of the Variational Garrote to a Multiple Measurement Vectors Model. SCAI 2013: 105-114 - [i7]Radu Dragusin, Paula Petcu, Christina Lioma, Birger Larsen, Henrik Jørgensen, Ingemar J. Cox, Lars Kai Hansen, Peter Ingwersen, Ole Winther:
FindZebra: A search engine for rare diseases. CoRR abs/1303.3229 (2013) - [i6]Arkadiusz Stopczynski, Carsten Stahlhut, Jakob Eg Larsen, Michael Kai Petersen, Lars Kai Hansen:
The Smartphone Brain Scanner: A Mobile Real-time Neuroimaging System. CoRR abs/1304.0357 (2013) - [i5]Jerónimo Arenas-García, Kaare Brandt Petersen, Gustavo Camps-Valls, Lars Kai Hansen:
Kernel Multivariate Analysis Framework for Supervised Subspace Learning: A Tutorial on Linear and Kernel Multivariate Methods. CoRR abs/1310.5089 (2013) - [i4]Bjarne Ørum Fruergaard, Toke Jansen Hansen, Lars Kai Hansen:
Dimensionality reduction for click-through rate prediction: Dense versus sparse representation. CoRR abs/1311.6976 (2013) - 2012
- [j49]Morten Mørup, Lars Kai Hansen:
Archetypal analysis for machine learning and data mining. Neurocomputing 80: 54-63 (2012) - [j48]Peter Mondrup Rasmussen, Trine Julie Abrahamsen, Kristoffer Hougaard Madsen, Lars Kai Hansen:
Nonlinear denoising and analysis of neuroimages with kernel principal component analysis and pre-image estimation. NeuroImage 60(3): 1807-1818 (2012) - [j47]Peter Mondrup Rasmussen, Lars Kai Hansen, Kristoffer Hougaard Madsen, Nathan William Churchill, Stephen C. Strother:
Model sparsity and brain pattern interpretation of classification models in neuroimaging. Pattern Recognit. 45(6): 2085-2100 (2012) - [j46]Kasper Winther Jørgensen, Lars Kai Hansen:
Model Selection for Gaussian Kernel PCA Denoising. IEEE Trans. Neural Networks Learn. Syst. 23(1): 163-168 (2012) - [c93]Peter Mondrup Rasmussen, Tanya Schmah, Kristoffer Hougaard Madsen, Torben Ellegaard Lund, Grigori Yourganov, Stephen C. Strother, Lars Kai Hansen:
Visualization of Nonlinear Classification Models in Neuroimaging - Signed Sensitivity Maps. BIOSIGNALS 2012: 254-263 - [c92]Pablo Garcia-Moreno, Antonio Artés-Rodríguez, Lars Kai Hansen:
A Hold-out method to correct PCA variance inflation. CIP 2012: 1-6 - [c91]Lars Kai Hansen:
Attention: A machine learning perspective. CIP 2012: 1-6 - [c90]Tue Herlau, Morten Mørup, Mikkel N. Schmidt, Lars Kai Hansen:
Detecting hierarchical structure in networks. CIP 2012: 1-6 - [c89]Jair Montoya-Martínez, Antonio Artés-Rodríguez, Lars Kai Hansen, Massimiliano Pontil:
Structured sparsity regularization approach to the EEG inverse problem. CIP 2012: 1-6 - [c88]Michael Kai Petersen, Lars Kai Hansen:
Cognitive semantic networks: Emotional verbs throw a tantrum but don't bite. CIP 2012: 1-6 - [c87]Carsten Stahlhut, Hagai Thomas Attias, Arkadiusz Stopczynski, Michael Kai Petersen, Jakob Eg Larsen, Lars Kai Hansen:
An evaluation of EEG scanner's dependence on the imaging technique, forward model computation method, and array dimensionality. EMBC 2012: 1538-1541 - [c86]Kasper Winther Andersen, Morten Mørup, Hartwig R. Siebner, Kristoffer Hougaard Madsen, Lars Kai Hansen:
Identifying modular relations in complex brain networks. MLSP 2012: 1-6 - [c85]Tue Herlau, Morten Mørup, Mikkel N. Schmidt, Lars Kai Hansen:
Modelling dense relational data. MLSP 2012: 1-6 - [p2]Jan Larsen, Claus Svarer, Lars Nonboe Andersen, Lars Kai Hansen:
Adaptive Regularization in Neural Network Modeling. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 111-130 - 2011
- [j45]Trine Julie Abrahamsen, Lars Kai Hansen:
A Cure for Variance Inflation in High Dimensional Kernel Principal Component Analysis. J. Mach. Learn. Res. 12: 2027-2044 (2011) - [j44]Peter Mondrup Rasmussen, Kristoffer Hougaard Madsen, Torben Ellegaard Lund, Lars Kai Hansen:
Visualization of nonlinear kernel models in neuroimaging by sensitivity maps. NeuroImage 55(3): 1120-1131 (2011) - [j43]Trine Julie Abrahamsen, Lars Kai Hansen:
Sparse non-linear denoising: Generalization performance and pattern reproducibility in functional MRI. Pattern Recognit. Lett. 32(15): 2080-2085 (2011) - [j42]Trine Julie Abrahamsen, Lars Kai Hansen:
Regularized Pre-image Estimation for Kernel PCA De-noising - Input Space Regularization and Sparse Reconstruction. J. Signal Process. Syst. 65(3): 403-412 (2011) - [j41]Carsten Stahlhut, Morten Mørup, Ole Winther, Lars Kai Hansen:
Simultaneous EEG Source and Forward Model Reconstruction (SOFOMORE) Using a Hierarchical Bayesian Approach. J. Signal Process. Syst. 65(3): 431-444 (2011) - [c84]Arkadiusz Stopczynski, Jakob Eg Larsen, Carsten Stahlhut, Michael Kai Petersen, Lars Kai Hansen:
A Smartphone Interface for a Wireless EEG Headset with Real-Time 3D Reconstruction. ACII (2) 2011: 317-318 - [c83]Michael Kai Petersen, Carsten Stahlhut, Arkadiusz Stopczynski, Jakob Eg Larsen, Lars Kai Hansen:
Smartphones Get Emotional: Mind Reading Images and Reconstructing the Neural Sources. ACII (2) 2011: 578-587 - [c82]Morten Mørup, Lars Kai Hansen, Kristoffer Hougaard Madsen:
Frequency constrained ShiftCP modeling of neuroimaging data. ACSCC 2011: 127-131 - [c81]Morten Mørup, Lars Kai Hansen, Kristoffer Hougaard Madsen:
Modeling latency and shape changes in trial based neuroimaging data. ACSCC 2011: 439-443 - [c80]Lars Kai Hansen, Seliz G. Karadogan, Letizia Marchegiani:
What to measure next to improve decision making? On top-down task driven feature saliency. CCMB 2011: 81-87 - [c79]Michael Kai Petersen, Lars Kai Hansen:
Emotional nodes among lines of lyrics. FG 2011: 821-826 - [c78]Seliz G. Karadogan, Letizia Marchegiani, Lars Kai Hansen, Jan Larsen:
How efficient is estimation with missing data? ICASSP 2011: 2260-2263 - [c77]Letizia Marchegiani, Seliz G. Karadogan, Tobias Andersen, Jan Larsen, Lars Kai Hansen:
The Role of Top-Down Attention in the Cocktail Party: Revisiting Cherry's Experiment after Sixty Years. ICMLA (1) 2011: 183-188 - [c76]Toke Jansen Hansen, Trine Julie Abrahamsen, Lars Kai Hansen:
A randomized heuristic for kernel parameter selection with large-scale multi-class data. MLSP 2011: 1-6 - [c75]Toke Jansen Hansen, Morten Mørup, Lars Kai Hansen:
Non-parametric co-clustering of large scale sparse bipartite networks on the GPU. MLSP 2011: 1-6 - [c74]Seliz G. Karadogan, Letizia Marchegiani, Jan Larsen, Lars Kai Hansen:
Top-down attentionwith features missing at random. MLSP 2011: 1-6 - [c73]Morten Mørup, Mikkel N. Schmidt, Lars Kai Hansen:
Infinite multiple membership relational modeling for complex networks. MLSP 2011: 1-6 - [c72]Bjarne Ørum Wahlgreen, Lars Kai Hansen:
Large scale topic modeling made practical. MLSP 2011: 1-6 - [c71]Toke Jansen Hansen, Lars Kai Hansen, Kristoffer Hougaard Madsen:
Decoding Complex Cognitive States Online by Manifold Regularization in Real-Time fMRI. MLINI 2011: 76-83 - [c70]Kasper Winther Andersen, Kristoffer Hougaard Madsen, Hartwig R. Siebner, Lars Kai Hansen, Morten Mørup:
Identification of Functional Clusters in the Striatum Using Infinite Relational Modeling. MLINI 2011: 226-233 - [c69]Trine Julie Abrahamsen, Lars Kai Hansen:
Restoring the Generalizability of SVM Based Decoding in High Dimensional Neuroimage Data. MLINI 2011: 256-263 - [i3]Lars Kai Hansen, Adam Arvidsson, Finn Årup Nielsen, Elanor Colleoni, Michael Etter:
Good Friends, Bad News - Affect and Virality in Twitter. CoRR abs/1101.0510 (2011) - [i2]Morten Mørup, Mikkel N. Schmidt, Lars Kai Hansen:
Infinite Multiple Membership Relational Modeling for Complex Networks. CoRR abs/1101.5097 (2011) - 2010
- [c68]Michael Kai Petersen, Morten Mørup, Lars Kai Hansen:
Latent semantics as cognitive components. CIP 2010: 434-439 - [c67]Ingemar J. Cox, Jianhan Zhu, Ruoxun Fu, Lars Kai Hansen:
Improving Query Correctness Using Centralized Probably Approximately Correct (PAC) Search. ECIR 2010: 265-280 - [c66]Carsten Stahlhut, Hagai Attias, David P. Wipf, Lars Kai Hansen, Srikantan S. Nagarajan:
Sparse Spatio-temporal Inference of Electromagnetic Brain Sources. MLMI 2010: 157-164 - [c65]Morten Mørup, Kristoffer Hougaard Madsen, Anne-Marie Dogonowski, Hartwig R. Siebner, Lars Kai Hansen:
Infinite Relational Modeling of Functional Connectivity in Resting State fMRI. NIPS 2010: 1750-1758 - [i1]Christian Walder, Ricardo Henao, Morten Mørup, Lars Kai Hansen:
Semi-Supervised Kernel PCA. CoRR abs/1008.1398 (2010)
2000 – 2009
- 2009
- [c64]Bartlomiej Wilkowski, Marcin Szewczyk, Peter Mondrup Rasmussen, Lars Kai Hansen, Finn Årup Nielsen:
Coordinate-based Meta-analytic search for the SPM Neuroimaging Pipeline - The BredeQuery Plugin for SPM5. HEALTHINF 2009: 11-17 - [c63]Bartlomiej Wilkowski, Marcin Szewczyk, Peter Mondrup Rasmussen, Lars Kai Hansen, Finn Årup Nielsen:
BredeQuery: Coordinate-Based Meta-analytic Search of Neuroscientific Literature from the SPM Environment. BIOSTEC (Selected Papers) 2009: 314-324 - [c62]Troels Bjerre, Jonas Henriksen, Carsten Haagen Nielsen, Peter Mondrup Rasmussen, Lars Kai Hansen, Kristoffer Hougaard Madsen:
Unified ICA-SPM Analysis of fMRI Experiments - Implementation of an ICA Graphical user Interface for the SPM Pipeline. BIOSIGNALS 2009: 316-321 - [c61]Morten Mørup, Lars Kai Hansen:
Tuning pruning in sparse non-negative matrix factorization. EUSIPCO 2009: 1923-1927 - [c60]Ingemar J. Cox, Ruoxun Fu, Lars Kai Hansen:
Probably Approximately Correct Search. ICTIR 2009: 2-16 - [c59]Mikkel N. Schmidt, Ole Winther, Lars Kai Hansen:
Bayesian Non-negative Matrix Factorization. ICA 2009: 540-547 - [c58]Carsten Stahlhut, Morten Mørup, Ole Winther, Lars Kai Hansen:
Sofomore: Combined EEG Source and Forward Model Reconstruction. ISBI 2009: 450-453 - 2008
- [j40]Hans Laurberg, Mads Græsbøll Christensen, Mark D. Plumbley, Lars Kai Hansen, Søren Holdt Jensen:
Theorems on Positive Data: On the Uniqueness of NMF. Comput. Intell. Neurosci. 2008 (2008) - [j39]Andreas Brinch Nielsen, Lars Kai Hansen:
Structure learning by pruning in independent component analysis. Neurocomputing 71(10-12): 2281-2290 (2008) - [j38]Tülay Adali, Z. Jane Wang, Martin J. McKeown, Philippe Ciuciu, Lars Kai Hansen, Andrzej Cichocki, Vincent D. Calhoun:
Introduction to the Issue on fMRI Analysis for Human Brain Mapping. IEEE J. Sel. Top. Signal Process. 2(6): 813-816 (2008) - [j37]Daniel J. Jacobsen, Lars Kai Hansen, Kristoffer Hougaard Madsen:
Bayesian Model Comparison in Nonlinear BOLD fMRI Hemodynamics. Neural Comput. 20(3): 738-755 (2008) - [j36]Morten Mørup, Lars Kai Hansen, Sidse Marie Arnfred:
Algorithms for Sparse Nonnegative Tucker Decompositions. Neural Comput. 20(8): 2112-2131 (2008) - [j35]Tim B. Dyrby, Egill Rostrup, William F. C. Baaré, Elisabeth C. W. van Straaten, Frederik Barkhof, Hugo Vrenken, Stefan Ropele, Reinhold Schmidt, Timo Erkinjuntti, Lars-Olof Wahlund, Leonardo Pantoni, Domenico Inzitari, Olaf B. Paulson, Lars Kai Hansen, Gunhild Waldemar:
Segmentation of age-related white matter changes in a clinical multi-center study. NeuroImage 41(2): 335-345 (2008) - [j34]Morten Mørup, Lars Kai Hansen, Sidse Marie Arnfred, Lek-Heng Lim, Kristoffer Hougaard Madsen:
Shift-invariant multilinear decomposition of neuroimaging data. NeuroImage 42(4): 1439-1450 (2008) - [j33]Thomas Beierholm, Albert H. Nuttall, Lars Kai Hansen:
Use and Subtleties of Saddlepoint Approximation for Minimum Mean-Square Error Estimation. IEEE Trans. Inf. Theory 54(12): 5778-5787 (2008) - [c57]Peter Mondrup Rasmussen, Morten Mørup, Lars Kai Hansen, Sidse Marie Arnfred:
Model Order Estimation for Independent Component Analysis of Epoched EEG Signals. BIOSIGNALS (2) 2008: 3-10 - [c56]Michael Kai Petersen, Lars Kai Hansen, Andrius Butkus:
Semantic Contours in Tracks Based on Emotional Tags. CMMR 2008: 45-66 - [c55]Jakob Eg Larsen, Søren Halling, Magnús Sigurðsson, Lars Kai Hansen:
MuZeeker: Adapting a Music Search Engine for Mobile Phones. WMMP 2008: 154-169 - [c54]Morten Mørup, Kristoffer Hougaard Madsen, Lars Kai Hansen:
Approximate L0 constrained non-negative matrix and tensor factorization. ISCAS 2008: 1328-1331 - [c53]Ling Feng, Andreas Brinch Nielsen, Lars Kai Hansen:
Vocal Segment Classification in Popular Music. ISMIR 2008: 121-126 - 2007
- [j32]Mads Dyrholm, Scott Makeig, Lars Kai Hansen:
Model Selection for Convolutive ICA with an Application to Spatiotemporal Analysis of EEG. Neural Comput. 19(4): 934-955 (2007) - [j31]Anders Meng, Peter Ahrendt, Jan Larsen, Lars Kai Hansen:
Temporal Feature Integration for Music Genre Classification. IEEE Trans. Speech Audio Process. 15(5): 1654-1664 (2007) - [j30]Ana S. Lukic, Miles N. Wernick, Yongyi Yang, Lars Kai Hansen, Konstantinos Arfanakis, Stephen C. Strother:
Effect of Spatial Alignment Transformations in PCA and ICA of Functional Neuroimages. IEEE Trans. Medical Imaging 26(8): 1058-1068 (2007) - [c52]Lars Kai Hansen, Tue Lehn-Schiøler, Kaare Brandt Petersen, Jerónimo Arenas-García, Jan Larsen, Søren Holdt Jensen:
Learning and clean-up in a large scale music database. EUSIPCO 2007: 946-950 - [c51]Morten Mørup, Kristoffer Hougaard Madsen, Lars Kai Hansen:
Shifted Independent Component Analysis. ICA 2007: 89-96 - [c50]Lasse Lohilahti Mølgaard, Kasper Winther Jørgensen, Lars Kai Hansen:
Castsearch - Context Based Spoken Document Retrieval. ICASSP (4) 2007: 93-96 - [c49]Bjarni Bödvarsson, Lars Kai Hansen, Claus Svarer, Gitte Moos Knudsen:
NMF on Positron Emission Tomography. ICASSP (1) 2007: 309-312 - [c48]Andreas Brinch Nielsen, Sigurdur Sigurdsson, Lars Kai Hansen, Jerónimo Arenas-García:
On the Relevance of Spectral Features for Instrument Classification. ICASSP (2) 2007: 485-488 - [c47]Hans Laurberg, Lars Kai Hansen:
On Affine Non-Negative Matrix Factorization. ICASSP (2) 2007: 653-656 - 2006
- [j29]Thomas Grotkjær, Ole Winther, Birgitte Regenberg, Jens Nielsen, Lars Kai Hansen:
Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm. Bioinform. 22(1): 58-67 (2006) - [j28]Rasmus Kongsgaard Olsson, Lars Kai Hansen:
Linear State-Space Models for Blind Source Separation. J. Mach. Learn. Res. 7: 2585-2602 (2006) - [j27]Morten Mørup, Lars Kai Hansen, Christoph S. Herrmann, Josef Parnas, Sidse Marie Arnfred:
Parallel Factor Analysis as an exploratory tool for wavelet transformed event-related EEG. NeuroImage 29(3): 938-947 (2006) - [c46]Lars Kai Hansen, Kristoffer Hougaard Madsen, Tue Lehn-Schiøler:
Adaptive regularization of noisy linear inverse problems. EUSIPCO 2006: 1-5 - [c45]Kasper Winther Jørgensen, Lasse Lohilahti Mølgaard, Lars Kai Hansen:
Unsupervised speaker change detection for broadcast news segmentation. EUSIPCO 2006: 1-5 - [c44]Mads Dyrholm, Scott Makeig, Lars Kai Hansen:
Model Structure Selection in Convolutive Mixtures. ICA 2006: 74-81 - [c43]Lars Kai Hansen, Ling Feng:
Cogito Componentiter Ergo Sum. ICA 2006: 446-453 - [c42]Rasmus Kongsgaard Olsson, Lars Kai Hansen:
Blind Separation of More Sources than Sensors in Convolutive Mixtures. ICASSP (5) 2006: 657-660 - [c41]Andreas Brinch Nielsen, Lars Kai Hansen, Ulrik Kjems:
Pitch Based Sound Classification. ICASSP (3) 2006: 788-791 - [c40]Ling Feng, Lars Kai Hansen:
Phonemes as Short Time Cognitive Components. ICASSP (5) 2006: 869-872 - [c39]Thomas Bøvith, Allan Aasbjerg Nielsen, Lars Kai Hansen, Søren Overgaard, Rashpal S. Gill:
Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output. IGARSS 2006: 511-514 - [c38]Daniel J. Jacobsen, Kristoffer Hougaard Madsen, Lars Kai Hansen:
Identification of non-linear models of neural activity in BOLD fMRI. ISBI 2006: 952-955 - [c37]Jerónimo Arenas-García, Jan Larsen, Lars Kai Hansen, Anders Meng:
Optimal filtering of dynamics in short-time features for music organization. ISMIR 2006: 290-295 - [c36]Tue Lehn-Schiøler, Jerónimo Arenas-García, Kaare Brandt Petersen, Lars Kai Hansen:
A Genre Classification Plug-in for Data Collection. ISMIR 2006: 320-321 - [c35]Jerónimo Arenas-García, Kaare Brandt Petersen, Lars Kai Hansen:
Sparse Kernel Orthonormalized PLS for feature extraction in large data sets. NIPS 2006: 33-40 - 2005
- [j26]Kaare Brandt Petersen, Ole Winther, Lars Kai Hansen:
On the Slow Convergence of EM and VBEM in Low-Noise Linear Models. Neural Comput. 17(9): 1921-1926 (2005) - [j25]Finn Årup Nielsen, Daniela Balslev, Lars Kai Hansen:
Mining the posterior cingulate: Segregation between memory and pain components. NeuroImage 27(3): 520-532 (2005) - [c34]Ling Feng, Lars Kai Hansen:
On Low-level Cognitive Components of Speech. CIMCA/IAWTIC 2005: 852-858 - 2004
- [j24]Finn Årup Nielsen, Lars Kai Hansen:
Finding related functional neuroimaging volumes. Artif. Intell. Medicine 30(2): 141-151 (2004) - [j23]Finn Årup Nielsen, Lars Kai Hansen, Daniela Balslev:
Mining for associations between text and brain activation in a functional neuroimaging database. Neuroinformatics 2(4): 369-379 (2004) - [j22]Sigurdur Sigurdsson, Peter Alshede Philipsen, Lars Kai Hansen, Jan Larsen, Monika Gniadecka, Hans-Christian Wulf:
Detection of skin cancer by classification of Raman spectra. IEEE Trans. Biomed. Eng. 51(10): 1784-1793 (2004) - [c33]Rasmus Kongsgaard Olsson, Lars Kai Hansen:
Probabilistic blind deconvolution of non-stationary sources. EUSIPCO 2004: 1697-1700 - [c32]Mads Dyrholm, Lars Kai Hansen:
CICAAR: Convolutive ICA with an Auto-regressive Inverse Model. ICA 2004: 594-601 - [c31]Rasmus Kongsgaard Olsson, Lars Kai Hansen:
Estimating the Number of Sources in a Noisy Convolutive Mixture Using BIC. ICA 2004: 618-625 - [c30]Michael Syskind Pedersen, Ulrik Kjems, Karsten Boye Rasmussen, Lars Kai Hansen:
Semi-blind source separation using head-related transfer functions [speech signal separation]. ICASSP (5) 2004: 713-716 - [c29]Rasmus Elsborg Madsen, Sigurdur Sigurdsson, Lars Kai Hansen, Jan Larsen:
Pruning The Vocabulary For Better Context Recognition. ICPR (2) 2004: 483-488 - [c28]Tue Lehn-Schiøler, Lars Kai Hansen, Jan Larsen:
Mapping from Speech to Images Using Continuous State Space Models. MLMI 2004: 136-145 - [c27]Rasmus Kongsgaard Olsson, Lars Kai Hansen:
A Harmonic Excitation State-Space Approach to Blind Separation of Speech. NIPS 2004: 993-1000 - 2003
- [j21]Stephen LaConte, Jon R. Anderson, Suraj Muley, James Ashe, Sally Frutiger, Kelly Rehm, Lars Kai Hansen, Essa Yacoub, Xiaoping Hu, David A. Rottenberg, Stephen C. Strother:
The Evaluation of Preprocessing Choices in Single-Subject BOLD fMRI Using NPAIRS Performance Metrics. NeuroImage 18(1): 10-27 (2003) - [c26]Lars Kai Hansen, Mads Dyrholm:
A prediction matrix approach to convolutive ICA. NNSP 2003: 249-258 - 2002
- [j20]Lars Kai Hansen, Finn Årup Nielsen, Jan Larsen:
Exploring fMRI data for periodic signal components. Artif. Intell. Medicine 25(1): 35-44 (2002) - [j19]Pedro A. d. F. R. Højen-Sørensen, Ole Winther, Lars Kai Hansen:
Analysis of functional neuroimages using ICA with adaptive binary sources. Neurocomputing 49(1-4): 213-225 (2002) - [j18]Mads Nielsen, Lars Kai Hansen, Peter Johansen, Jon Sporring:
Guest Editorial: Special Issue on Statistics of Shapes and Textures. J. Math. Imaging Vis. 17(2): 87 (2002) - [j17]Pedro A. d. F. R. Højen-Sørensen, Ole Winther, Lars Kai Hansen:
Mean-Field Approaches to Independent Component Analysis. Neural Comput. 14(4): 889-918 (2002) - [j16]Stephen C. Strother, Jon R. Anderson, Lars Kai Hansen, Ulrik Kjems, Rafal Kustra, John J. Sidtis, Sally Frutiger, Suraj Muley, Stephen LaConte, David A. Rottenberg:
The Quantitative Evaluation of Functional Neuroimaging Experiments: The NPAIRS Data Analysis Framework. NeuroImage 15(4): 747-771 (2002) - [j15]Ulrik Kjems, Lars Kai Hansen, Jon R. Anderson, Sally Frutiger, Suraj Muley, John J. Sidtis, David A. Rottenberg, Stephen C. Strother:
The Quantitative Evaluation of Functional Neuroimaging Experiments: Mutual Information Learning Curves. NeuroImage 15(4): 772-786 (2002) - [c25]Joaquin Quiñonero Candela, Lars Kai Hansen:
Time series prediction based on the Relevance Vector Machine with adaptive kernels. ICASSP 2002: 985-988 - [c24]Sigurdur Sigurdsson, Jan Larsen, Lars Kai Hansen, Peter Alshede Philipsen, Hans-Christian Wulf:
Outlier estimation and detection application to skin lesion classification. ICASSP 2002: 1049-1052 - [c23]Ana S. Lukic, Lars Kai Hansen, Miles N. Wernick, Stephen C. Strother:
An ICA algorithm for analyzing multiple data sets. ICIP (2) 2002: 821-824 - [c22]Ana S. Lukic, Miles N. Wernick, Lars Kai Hansen, Jon R. Anderson, Stephen C. Strother:
A spatially robust ICA algorithm for multiple fMRI data sets. ISBI 2002: 839-842 - [c21]Anna Szymkowiak-Have, Jan Larsen, Lars Kai Hansen, Peter Alshede Philipsen, Elisabeth Thieden, Hans-Christian Wulf:
Clustering of Sun exposure measurements. NNSP 2002: 727-735 - [c20]Thomas Kolenda, Lars Kai Hansen, Jan Larsen, Ole Winther:
Independent component analysis for understanding multimedia content. NNSP 2002: 757-766 - 2001
- [c19]Lars Kai Hansen, Jan Larsen, Thomas Kolenda:
Blind detection of independent dynamic components. ICASSP 2001: 3197-3200 - [c18]Thomas Fabricius, Preben Kidmose, Lars Kai Hansen:
Dynamic components of linear stable mixtures from fractional low order moments. ICASSP 2001: 3957-3960 - 2000
- [j14]Cyril Goutte, Finn Årup Nielsen, Lars Kai Hansen:
Modelling the Haemodynamic Response in fMRI with Smooth FIR Filters. IEEE Trans. Medical Imaging 19(12): 1188-1201 (2000) - [c17]Lars Kai Hansen, Sigurdur Sigurdsson, Thomas Kolenda, Finn Årup Nielsen, Ulrik Kjems, Jan Larsen:
Modeling text with generalizable Gaussian mixtures. ICASSP 2000: 3494-3497 - [c16]Pedro A. d. F. R. Højen-Sørensen, Ole Winther, Lars Kai Hansen:
Ensemble Learning and Linear Response Theory for ICA. NIPS 2000: 542-548 - [c15]Ulrik Kjems, Lars Kai Hansen, Stephen C. Strother:
Generalizable Singular Value Decomposition for Ill-posed Datasets. NIPS 2000: 549-555
1990 – 1999
- 1999
- [j13]Ulrik Kjems, Stephen C. Strother, Jon R. Anderson, Ian Law, Lars Kai Hansen:
Enhancing the Multivariate Signal of [15O] water PET Studies with a New Non-Linear Neuroanatomical Registration Algorithm. IEEE Trans. Medical Imaging 18(4): 306-319 (1999) - [c14]Lars Nonboe Andersen, Whitlow W. L. Au, Jan Larsen, Lars Kai Hansen:
Sonar discrimination of cylinders from different angles using neural networks. ICASSP 1999: 1121-1124 - [c13]Lars Kai Hansen:
Bayesian Averaging is Well-Temperated. NIPS 1999: 265-271 - [c12]Pedro A. d. F. R. Højen-Sørensen, Lars Kai Hansen, Carl Edward Rasmussen:
Bayesian Modelling of fMRI lime Series. NIPS 1999: 754-760 - 1998
- [j12]Mads Hintz-Madsen, Lars Kai Hansen, Jan Larsen, Morten With Pedersen, Michael Larsen:
Neural classifier construction using regularization, pruning and test error estimation. Neural Networks 11(9): 1659-1670 (1998) - [j11]Jens E. Wilhjelm, M.-L. M. Grønholdt, B. Wiebe, S. K. Jespersen, Lars Kai Hansen, H. Sillesen:
Quantitative Analysis of Ultrasound B-mode images of Carotid Atherosclerotic Plaque: Correlation with Visual Classification and Histological Examination. IEEE Trans. Medical Imaging 17(6): 910-922 (1998) - [c11]Jan Larsen, Lars Nonboe Andersen, Mads Hintz-Madsen, Lars Kai Hansen:
Design of robust neural network classifiers. ICASSP 1998: 1205-1208 - 1997
- [j10]Jan Gorodkin, Lars Kai Hansen, Benny Lautrup, Sara A. Solla:
Universal Distribution of Saliencies for Pruning in Layered Neural Networks. Int. J. Neural Syst. 8(5-6): 489-498 (1997) - [j9]Cyril Goutte, Lars Kai Hansen:
Regularization with a Pruning Prior. Neural Networks 10(6): 1053-1059 (1997) - [j8]Jan Larsen, Lars Kai Hansen:
Generalization: The Hidden Agenda of Learning. IEEE Signal Process. Mag. 14(6): 43-45 (1997) - [c10]Finn Årup Nielsen, Lars Kai Hansen:
Interactive Information Visualization in Neuroimaging. Workshop on New Paradigms in Information Visualization and Manipulation 1997: 62-65 - [c9]Lars Kai Hansen, Jan Larsen, Torben Fog:
Early stop criterion from the bootstrap ensemble. ICASSP 1997: 3205-3208 - [c8]Niels J. S. Mørch, Lars Kai Hansen, Stephen C. Strother, Claus Svarer, David A. Rottenberg, Benny Lautrup, Robert L. Savoy, Olaf B. Paulson:
Nonlinear versus Linear Models in Functional Neuroimaging: Learning Curves and Generalization Crossover. IPMI 1997: 259-270 - 1996
- [j7]Lars Kai Hansen, Jan Larsen:
Linear unlearning for cross-validation. Adv. Comput. Math. 5(1): 269-280 (1996) - [c7]Lars Kai Hansen, Lars Nonboe Andersen, Ulrik Kjems, Jan Larsen:
Revisiting Boltzmann learning: parameter estimation in Markov random fields. ICASSP 1996: 3394-3397 - [c6]Lars Kai Hansen, Jan Larsen:
Unsupervised learning and generalization. ICNN 1996: 25-30 - [p1]Jan Larsen, Claus Svarer, Lars Nonboe Andersen, Lars Kai Hansen:
Adaptive Regularization in Neural Network Modeling. Neural Networks: Tricks of the Trade 1996: 113-132 - 1995
- [c5]Torben Fog, Jan Larsen, Lars Kai Hansen:
Training and evaluation of neural networks for multi-variate time series processing. ICNN 1995: 1194-1199 - [c4]Niels J. S. Mørch, Ulrik Kjems, Lars Kai Hansen, Claus Svarer, Ian Law, Benny Lautrup, Stephen C. Strother, Kelly Rehm:
Visualization of neural networks using saliency maps. ICNN 1995: 2085-2090 - [c3]Morten With Pedersen, Lars Kai Hansen, Jan Larsen:
Pruning with generalization based weight saliencies: gamma-OBD, gamma-OBS. NIPS 1995: 521-527 - 1994
- [j6]Lars Kai Hansen:
Book Review: "Time Series Prediction: Forecasting the Future and Understanding the Past", Eds. Andreas S. Weigend and Neil A. Gershenfeld. Int. J. Neural Syst. 5(2): 157-158 (1994) - [j5]Lars Kai Hansen, Carl Edward Rasmussen:
Pruning from Adaptive Regularization. Neural Comput. 6(6): 1223-1232 (1994) - [c2]Morten With Pedersen, Lars Kai Hansen:
Recurrent Networks: Second Order Properties and Pruning. NIPS 1994: 673-680 - 1993
- [j4]Peter Salamon, John C. Wootton, Andrzej K. Konopka, Lars Kai Hansen:
On the Robustness of Maximum Entropy Relationships for Complexity Distributions of Nucleotide Sequences. Comput. Chem. 17(2): 135-148 (1993) - [j3]Jan Gorodkin, Lars Kai Hansen, Anders Krogh, Claus Svarer, Ole Winther:
A Quantitative Study Of Pruning By Optimal Brain Damage. Int. J. Neural Syst. 4(2): 159-169 (1993) - [j2]Lars Kai Hansen:
Stochastic linear learning: Exact test and training error averages. Neural Networks 6(3): 393-396 (1993) - [c1]Claus Svarer, Lars Kai Hansen, Jan Larsen:
On design and evaluation of tapped-delay neural network architectures. ICNN 1993: 46-51 - 1990
- [j1]Lars Kai Hansen, Peter Salamon:
Neural Network Ensembles. IEEE Trans. Pattern Anal. Mach. Intell. 12(10): 993-1001 (1990)
Coauthor Index
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