Neural Network Ensembles. - Lars Kai Hansen; Peter Salamon (IEEE Trans. Pattern Anal. Mach. Intell., 1990)

On design and evaluation of tapped-delay neural network architectures. - Claus Svarer; Lars Kai Hansen; Jan Larsen (ICNN, 1993)

On the Robustness of Maximum Entropy Relationships for Complexity Distributions of Nucleotide Sequences. - Peter Salamon; John C. Wootton; Andrzej K. Konopka; Lars Kai Hansen (Comput. Chem., 1993)

A Quantitative Study Of Pruning By Optimal Brain Damage. - Jan Gorodkin; Lars Kai Hansen; Anders Krogh; Claus Svarer; Ole Winther (Int. J. Neural Syst., 1993)

Stochastic linear learning: Exact test and training error averages. - Lars Kai Hansen (Neural Networks, 1993)

Recurrent Networks: Second Order Properties and Pruning. - Morten With Pedersen; Lars Kai Hansen (NIPS, 1994)

Book Review: "Time Series Prediction: Forecasting the Future and Understanding the Past", Eds. Andreas S. Weigend and Neil A. Gershenfeld. - Lars Kai Hansen (Int. J. Neural Syst., 1994)

Pruning from Adaptive Regularization. - Lars Kai Hansen; Carl Edward Rasmussen (Neural Comput., 1994)

Training and evaluation of neural networks for multi-variate time series processing. - Torben Fog; Jan Larsen; Lars Kai Hansen (ICNN, 1995)

Visualization of neural networks using saliency maps. - Niels J. S. Mørch; Ulrik Kjems; Lars Kai Hansen; Claus Svarer; Ian Law; Benny Lautrup; Stephen C. Strother; Kelly Rehm (ICNN, 1995)

Pruning with generalization based weight saliencies: gamma-OBD, gamma-OBS. - Morten With Pedersen; Lars Kai Hansen; Jan Larsen (NIPS, 1995)

Revisiting Boltzmann learning: parameter estimation in Markov random fields. - Lars Kai Hansen; Lars Nonboe Andersen; Ulrik Kjems; Jan Larsen (ICASSP, 1996)

Unsupervised learning and generalization. - Lars Kai Hansen; Jan Larsen (ICNN, 1996)

Adaptive Regularization in Neural Network Modeling. - Jan Larsen; Claus Svarer; Lars Nonboe Andersen; Lars Kai Hansen (Neural Networks: Tricks of the Trade, 1996)

Linear unlearning for cross-validation. - Lars Kai Hansen; Jan Larsen (Adv. Comput. Math., 1996)

Interactive Information Visualization in Neuroimaging. - Finn Årup Nielsen; Lars Kai Hansen (Workshop on New Paradigms in Information Visualization and Manipulation, 1997)

Early stop criterion from the bootstrap ensemble. - Lars Kai Hansen; Jan Larsen; Torben Fog (ICASSP, 1997)

Nonlinear versus Linear Models in Functional Neuroimaging: Learning Curves and Generalization Crossover. - Niels J. S. Mørch; Lars Kai Hansen; Stephen C. Strother; Claus Svarer; David A. Rottenberg; Benny Lautrup; Robert L. Savoy; Olaf B. Paulson (IPMI, 1997)

Universal Distribution of Saliencies for Pruning in Layered Neural Networks. - Jan Gorodkin; Lars Kai Hansen; Benny Lautrup; Sara A. Solla (Int. J. Neural Syst., 1997)

Regularization with a Pruning Prior. - Cyril Goutte; Lars Kai Hansen (Neural Networks, 1997)

Generalization: The Hidden Agenda of Learning. - Jan Larsen; Lars Kai Hansen (IEEE Signal Process. Mag., 1997)

Design of robust neural network classifiers. - Jan Larsen; Lars Nonboe Andersen; Mads Hintz-Madsen; Lars Kai Hansen (ICASSP, 1998)

Neural classifier construction using regularization, pruning and test error estimation. - Mads Hintz-Madsen; Lars Kai Hansen; Jan Larsen; Morten With Pedersen; Michael Larsen (Neural Networks, 1998)

Quantitative Analysis of Ultrasound B-mode images of Carotid Atherosclerotic Plaque: Correlation with Visual Classification and Histological Examination. - Jens E. Wilhjelm; M.-L. M. Grønholdt; B. Wiebe; S. K. Jespersen; Lars Kai Hansen; H. Sillesen (IEEE Trans. Medical Imaging, 1998)

Sonar discrimination of cylinders from different angles using neural networks. - Lars Nonboe Andersen; Whitlow W. L. Au; Jan Larsen; Lars Kai Hansen (ICASSP, 1999)

Bayesian Averaging is Well-Temperated. - Lars Kai Hansen (NIPS, 1999)

Bayesian Modelling of fMRI lime Series. - Pedro A. d. F. R. Højen-Sørensen; Lars Kai Hansen; Carl Edward Rasmussen (NIPS, 1999)

Enhancing the Multivariate Signal of [15O] water PET Studies with a New Non-Linear Neuroanatomical Registration Algorithm. - Ulrik Kjems; Stephen C. Strother; Jon R. Anderson; Ian Law; Lars Kai Hansen (IEEE Trans. Medical Imaging, 1999)

Modeling text with generalizable Gaussian mixtures. - Lars Kai Hansen; Sigurdur Sigurdsson; Thomas Kolenda; Finn Årup Nielsen; Ulrik Kjems; Jan Larsen (ICASSP, 2000)

Ensemble Learning and Linear Response Theory for ICA. - Pedro A. d. F. R. Højen-Sørensen; Ole Winther; Lars Kai Hansen (NIPS, 2000)

Generalizable Singular Value Decomposition for Ill-posed Datasets. - Ulrik Kjems; Lars Kai Hansen; Stephen C. Strother (NIPS, 2000)

Modelling the Haemodynamic Response in fMRI with Smooth FIR Filters. - Cyril Goutte; Finn Årup Nielsen; Lars Kai Hansen (IEEE Trans. Medical Imaging, 2000)

Dynamic components of linear stable mixtures from fractional low order moments. - Thomas Fabricius; Preben Kidmose; Lars Kai Hansen (ICASSP, 2001)

Blind detection of independent dynamic components. - Lars Kai Hansen; Jan Larsen; Thomas Kolenda (ICASSP, 2001)

Time series prediction based on the Relevance Vector Machine with adaptive kernels. - Joaquin Quiñonero Candela; Lars Kai Hansen (ICASSP, 2002)

Outlier estimation and detection application to skin lesion classification. - Sigurdur Sigurdsson; Jan Larsen; Lars Kai Hansen; Peter Alshede Philipsen; Hans-Christian Wulf (ICASSP, 2002)

An ICA algorithm for analyzing multiple data sets. - Ana S. Lukic; Lars Kai Hansen; Miles N. Wernick; Stephen C. Strother (ICIP (2), 2002)

A spatially robust ICA algorithm for multiple fMRI data sets. - Ana S. Lukic; Miles N. Wernick; Lars Kai Hansen; Jon R. Anderson; Stephen C. Strother (ISBI, 2002)

Independent component analysis for understanding multimedia content. - Thomas Kolenda; Lars Kai Hansen; Jan Larsen; Ole Winther (NNSP, 2002)

Clustering of Sun exposure measurements. - Anna Szymkowiak-Have; Jan Larsen; Lars Kai Hansen; Peter Alshede Philipsen; Elisabeth Thieden; Hans-Christian Wulf (NNSP, 2002)

Exploring fMRI data for periodic signal components. - Lars Kai Hansen; Finn Årup Nielsen; Jan Larsen (Artif. Intell. Medicine, 2002)

Analysis of functional neuroimages using ICA with adaptive binary sources. - Pedro A. d. F. R. Højen-Sørensen; Ole Winther; Lars Kai Hansen (Neurocomputing, 2002)

Guest Editorial: Special Issue on Statistics of Shapes and Textures. - Mads Nielsen; Lars Kai Hansen; Peter Johansen; Jon Sporring (J. Math. Imaging Vis., 2002)

Mean-Field Approaches to Independent Component Analysis. - Pedro A. d. F. R. Højen-Sørensen; Ole Winther; Lars Kai Hansen (Neural Comput., 2002)

The Quantitative Evaluation of Functional Neuroimaging Experiments: Mutual Information Learning Curves. - Ulrik Kjems; Lars Kai Hansen; Jon R. Anderson; Sally Frutiger; Suraj Muley; John J. Sidtis; David A. Rottenberg; Stephen C. Strother (NeuroImage, 2002)

The Quantitative Evaluation of Functional Neuroimaging Experiments: The NPAIRS Data Analysis Framework. - 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 (NeuroImage, 2002)

A prediction matrix approach to convolutive ICA. - Lars Kai Hansen; Mads Dyrholm (NNSP, 2003)

The Evaluation of Preprocessing Choices in Single-Subject BOLD fMRI Using NPAIRS Performance Metrics. - Stephen LaConte; Jon R. Anderson; Suraj Muley; James Ashe; Sally Frutiger; Kelly Rehm; Lars Kai Hansen; Essa Yacoub; Xiaoping Hu 001; David A. Rottenberg; Stephen C. Strother (NeuroImage, 2003)

Probabilistic blind deconvolution of non-stationary sources. - Rasmus Kongsgaard Olsson; Lars Kai Hansen (EUSIPCO, 2004)

CICAAR: Convolutive ICA with an Auto-regressive Inverse Model. - Mads Dyrholm; Lars Kai Hansen (ICA, 2004)

Estimating the Number of Sources in a Noisy Convolutive Mixture Using BIC. - Rasmus Kongsgaard Olsson; Lars Kai Hansen (ICA, 2004)

Semi-blind source separation using head-related transfer functions [speech signal separation]. - Michael Syskind Pedersen; Ulrik Kjems; Karsten Boye Rasmussen; Lars Kai Hansen (ICASSP (5), 2004)

Pruning The Vocabulary For Better Context Recognition. - Rasmus Elsborg Madsen; Sigurdur Sigurdsson; Lars Kai Hansen; Jan Larsen (ICPR (2), 2004)

Mapping from Speech to Images Using Continuous State Space Models. - Tue Lehn-Schiøler; Lars Kai Hansen; Jan Larsen (MLMI, 2004)

A Harmonic Excitation State-Space Approach to Blind Separation of Speech. - Rasmus Kongsgaard Olsson; Lars Kai Hansen (NIPS, 2004)

Finding related functional neuroimaging volumes. - Finn Årup Nielsen; Lars Kai Hansen (Artif. Intell. Medicine, 2004)

Mining for associations between text and brain activation in a functional neuroimaging database. - Finn Årup Nielsen; Lars Kai Hansen; Daniela Balslev (Neuroinformatics, 2004)

Detection of skin cancer by classification of Raman spectra. - Sigurdur Sigurdsson; Peter Alshede Philipsen; Lars Kai Hansen; Jan Larsen; Monika Gniadecka; Hans-Christian Wulf (IEEE Trans. Biomed. Eng., 2004)

On Low-level Cognitive Components of Speech. - Ling Feng; Lars Kai Hansen (CIMCA/IAWTIC, 2005)

On the Slow Convergence of EM and VBEM in Low-Noise Linear Models. - Kaare Brandt Petersen; Ole Winther; Lars Kai Hansen (Neural Comput., 2005)

Mining the posterior cingulate: Segregation between memory and pain components. - Finn Årup Nielsen; Daniela Balslev; Lars Kai Hansen (NeuroImage, 2005)

Adaptive regularization of noisy linear inverse problems. - Lars Kai Hansen; Kristoffer Hougaard Madsen; Tue Lehn-Schiøler (EUSIPCO, 2006)

Unsupervised speaker change detection for broadcast news segmentation. - Kasper Winther Jørgensen; Lasse Lohilahti Mølgaard; Lars Kai Hansen (EUSIPCO, 2006)

Model Structure Selection in Convolutive Mixtures. - Mads Dyrholm; Scott Makeig; Lars Kai Hansen (ICA, 2006)

Cogito Componentiter Ergo Sum. - Lars Kai Hansen; Ling Feng (ICA, 2006)

Phonemes as Short Time Cognitive Components. - Ling Feng; Lars Kai Hansen (ICASSP (5), 2006)

Pitch Based Sound Classification. - Andreas Brinch Nielsen; Lars Kai Hansen; Ulrik Kjems (ICASSP (3), 2006)

Blind Separation of More Sources than Sensors in Convolutive Mixtures. - Rasmus Kongsgaard Olsson; Lars Kai Hansen (ICASSP (5), 2006)

Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output. - Thomas Bøvith; Allan Aasbjerg Nielsen; Lars Kai Hansen; Søren Overgaard; Rashpal S. Gill (IGARSS, 2006)

Identification of non-linear models of neural activity in BOLD fMRI. - Daniel J. Jacobsen; Kristoffer Hougaard Madsen; Lars Kai Hansen (ISBI, 2006)

Optimal filtering of dynamics in short-time features for music organization. - Jerónimo Arenas-García; Jan Larsen; Lars Kai Hansen; Anders Meng (ISMIR, 2006)

A Genre Classification Plug-in for Data Collection. - Tue Lehn-Schiøler; Jerónimo Arenas-García; Kaare Brandt Petersen; Lars Kai Hansen (ISMIR, 2006)

Sparse Kernel Orthonormalized PLS for feature extraction in large data sets. - Jerónimo Arenas-García; Kaare Brandt Petersen; Lars Kai Hansen (NIPS, 2006)

Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm. - Thomas Grotkjær; Ole Winther; Birgitte Regenberg; Jens Nielsen; Lars Kai Hansen (Bioinform., 2006)

Linear State-Space Models for Blind Source Separation. - Rasmus Kongsgaard Olsson; Lars Kai Hansen (J. Mach. Learn. Res., 2006)

Parallel Factor Analysis as an exploratory tool for wavelet transformed event-related EEG. - Morten Mørup; Lars Kai Hansen; Christoph S. Herrmann; Josef Parnas; Sidse Marie Arnfred (NeuroImage, 2006)

Learning and clean-up in a large scale music database. - Lars Kai Hansen; Tue Lehn-Schiøler; Kaare Brandt Petersen; Jerónimo Arenas-García; Jan Larsen; Søren Holdt Jensen (EUSIPCO, 2007)

Shifted Independent Component Analysis. - Morten Mørup; Kristoffer Hougaard Madsen; Lars Kai Hansen (ICA, 2007)

NMF on Positron Emission Tomography. - Bjarni Bödvarsson; Lars Kai Hansen; Claus Svarer; Gitte Moos Knudsen (ICASSP (1), 2007)

On Affine Non-Negative Matrix Factorization. - Hans Laurberg; Lars Kai Hansen (ICASSP (2), 2007)

Castsearch - Context Based Spoken Document Retrieval. - Lasse Lohilahti Mølgaard; Kasper Winther Jørgensen; Lars Kai Hansen (ICASSP (4), 2007)

On the Relevance of Spectral Features for Instrument Classification. - Andreas Brinch Nielsen; Sigurdur Sigurdsson; Lars Kai Hansen; Jerónimo Arenas-García (ICASSP (2), 2007)

Model Selection for Convolutive ICA with an Application to Spatiotemporal Analysis of EEG. - Mads Dyrholm; Scott Makeig; Lars Kai Hansen (Neural Comput., 2007)

Temporal Feature Integration for Music Genre Classification. - Anders Meng; Peter Ahrendt; Jan Larsen; Lars Kai Hansen (IEEE Trans. Speech Audio Process., 2007)

Effect of Spatial Alignment Transformations in PCA and ICA of Functional Neuroimages. - Ana S. Lukic; Miles N. Wernick; Yongyi Yang; Lars Kai Hansen; Konstantinos Arfanakis; Stephen C. Strother (IEEE Trans. Medical Imaging, 2007)

Model Order Estimation for Independent Component Analysis of Epoched EEG Signals. - Peter Mondrup Rasmussen; Morten Mørup; Lars Kai Hansen; Sidse Marie Arnfred (BIOSIGNALS (2), 2008)

Semantic Contours in Tracks Based on Emotional Tags. - Michael Kai Petersen; Lars Kai Hansen; Andrius Butkus (CMMR, 2008)

MuZeeker: Adapting a Music Search Engine for Mobile Phones. - Jakob Eg Larsen; Søren Halling; Magnús Sigurðsson; Lars Kai Hansen (WMMP, 2008)

Approximate L0 constrained non-negative matrix and tensor factorization. - Morten Mørup; Kristoffer Hougaard Madsen; Lars Kai Hansen (ISCAS, 2008)

Vocal Segment Classification in Popular Music. - Ling Feng; Andreas Brinch Nielsen; Lars Kai Hansen (ISMIR, 2008)

Theorems on Positive Data: On the Uniqueness of NMF. - Hans Laurberg; Mads Græsbøll Christensen; Mark D. Plumbley; Lars Kai Hansen; Søren Holdt Jensen (Comput. Intell. Neurosci., 2008)

Structure learning by pruning in independent component analysis. - Andreas Brinch Nielsen; Lars Kai Hansen (Neurocomputing, 2008)

Introduction to the Issue on fMRI Analysis for Human Brain Mapping. - Tülay Adali; Z. Jane Wang 001; Martin J. McKeown; Philippe Ciuciu; Lars Kai Hansen; Andrzej Cichocki; Vincent D. Calhoun (IEEE J. Sel. Top. Signal Process., 2008)

Bayesian Model Comparison in Nonlinear BOLD fMRI Hemodynamics. - Daniel J. Jacobsen; Lars Kai Hansen; Kristoffer Hougaard Madsen (Neural Comput., 2008)

Algorithms for Sparse Nonnegative Tucker Decompositions. - Morten Mørup; Lars Kai Hansen; Sidse Marie Arnfred (Neural Comput., 2008)

Segmentation of age-related white matter changes in a clinical multi-center study. - 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; et al. (NeuroImage, 2008)

Shift-invariant multilinear decomposition of neuroimaging data. - Morten Mørup; Lars Kai Hansen; Sidse Marie Arnfred; Lek-Heng Lim; Kristoffer Hougaard Madsen (NeuroImage, 2008)

Use and Subtleties of Saddlepoint Approximation for Minimum Mean-Square Error Estimation. - Thomas Beierholm; Albert H. Nuttall; Lars Kai Hansen (IEEE Trans. Inf. Theory, 2008)

Unified ICA-SPM Analysis of fMRI Experiments - Implementation of an ICA Graphical user Interface for the SPM Pipeline. - Troels Bjerre; Jonas Henriksen; Carsten Haagen Nielsen; Peter Mondrup Rasmussen; Lars Kai Hansen; Kristoffer Hougaard Madsen (BIOSIGNALS, 2009)

Coordinate-based Meta-analytic search for the SPM Neuroimaging Pipeline - The BredeQuery Plugin for SPM5. - Bartlomiej Wilkowski; Marcin Szewczyk; Peter Mondrup Rasmussen; Lars Kai Hansen; Finn Årup Nielsen (HEALTHINF, 2009)

BredeQuery: Coordinate-Based Meta-analytic Search of Neuroscientific Literature from the SPM Environment. - Bartlomiej Wilkowski; Marcin Szewczyk; Peter Mondrup Rasmussen; Lars Kai Hansen; Finn Årup Nielsen (BIOSTEC (Selected Papers), 2009)

Tuning pruning in sparse non-negative matrix factorization. - Morten Mørup; Lars Kai Hansen (EUSIPCO, 2009)

Probably Approximately Correct Search. - Ingemar J. Cox; Ruoxun Fu; Lars Kai Hansen (ICTIR, 2009)

Bayesian Non-negative Matrix Factorization. - Mikkel N. Schmidt; Ole Winther; Lars Kai Hansen (ICA, 2009)

Sofomore: Combined EEG Source and Forward Model Reconstruction. - Carsten Stahlhut; Morten Mørup; Ole Winther; Lars Kai Hansen (ISBI, 2009)

Latent semantics as cognitive components. - Michael Kai Petersen; Morten Mørup; Lars Kai Hansen (CIP, 2010)

Improving Query Correctness Using Centralized Probably Approximately Correct (PAC) Search. - Ingemar J. Cox; Jianhan Zhu; Ruoxun Fu; Lars Kai Hansen (ECIR, 2010)

Sparse Spatio-temporal Inference of Electromagnetic Brain Sources. - Carsten Stahlhut; Hagai Attias; David P. Wipf; Lars Kai Hansen; Srikantan S. Nagarajan (MLMI, 2010)

Infinite Relational Modeling of Functional Connectivity in Resting State fMRI. - Morten Mørup; Kristoffer Hougaard Madsen; Anne-Marie Dogonowski; Hartwig R. Siebner; Lars Kai Hansen (NIPS, 2010)

Semi-Supervised Kernel PCA - Christian Walder; Ricardo Henao; Morten Mørup; Lars Kai Hansen (CoRR, 2010)

Smartphones Get Emotional: Mind Reading Images and Reconstructing the Neural Sources. - Michael Kai Petersen; Carsten Stahlhut; Arkadiusz Stopczynski; Jakob Eg Larsen; Lars Kai Hansen (ACII (2), 2011)

A Smartphone Interface for a Wireless EEG Headset with Real-Time 3D Reconstruction. - Arkadiusz Stopczynski; Jakob Eg Larsen; Carsten Stahlhut; Michael Kai Petersen; Lars Kai Hansen (ACII (2), 2011)

Frequency constrained ShiftCP modeling of neuroimaging data. - Morten Mørup; Lars Kai Hansen; Kristoffer Hougaard Madsen (ACSCC, 2011)

Modeling latency and shape changes in trial based neuroimaging data. - Morten Mørup; Lars Kai Hansen; Kristoffer Hougaard Madsen (ACSCC, 2011)

What to measure next to improve decision making? On top-down task driven feature saliency. - Lars Kai Hansen; Seliz G. Karadogan; Letizia Marchegiani (CCMB, 2011)

Emotional nodes among lines of lyrics. - Michael Kai Petersen; Lars Kai Hansen (FG, 2011)

How efficient is estimation with missing data? - Seliz G. Karadogan; Letizia Marchegiani; Lars Kai Hansen; Jan Larsen (ICASSP, 2011)

The Role of Top-Down Attention in the Cocktail Party: Revisiting Cherry's Experiment after Sixty Years. - Letizia Marchegiani; Seliz G. Karadogan; Tobias Andersen; Jan Larsen; Lars Kai Hansen (ICMLA (1), 2011)

A randomized heuristic for kernel parameter selection with large-scale multi-class data. - Toke Jansen Hansen; Trine Julie Abrahamsen; Lars Kai Hansen (MLSP, 2011)

Non-parametric co-clustering of large scale sparse bipartite networks on the GPU. - Toke Jansen Hansen; Morten Mørup; Lars Kai Hansen (MLSP, 2011)

Top-down attentionwith features missing at random. - Seliz G. Karadogan; Letizia Marchegiani; Jan Larsen; Lars Kai Hansen (MLSP, 2011)

Infinite multiple membership relational modeling for complex networks. - Morten Mørup; Mikkel N. Schmidt; Lars Kai Hansen (MLSP, 2011)

Large scale topic modeling made practical. - Bjarne Ørum Wahlgreen; Lars Kai Hansen (MLSP, 2011)

Restoring the Generalizability of SVM Based Decoding in High Dimensional Neuroimage Data. - Trine Julie Abrahamsen; Lars Kai Hansen (MLINI, 2011)

Identification of Functional Clusters in the Striatum Using Infinite Relational Modeling. - Kasper Winther Andersen; Kristoffer Hougaard Madsen; Hartwig R. Siebner; Lars Kai Hansen; Morten Mørup (MLINI, 2011)

Decoding Complex Cognitive States Online by Manifold Regularization in Real-Time fMRI. - Toke Jansen Hansen; Lars Kai Hansen; Kristoffer Hougaard Madsen (MLINI, 2011)

Good Friends, Bad News - Affect and Virality in Twitter - Lars Kai Hansen; Adam Arvidsson; Finn Årup Nielsen; Elanor Colleoni; Michael Etter (CoRR, 2011)

A Cure for Variance Inflation in High Dimensional Kernel Principal Component Analysis. - Trine Julie Abrahamsen; Lars Kai Hansen (J. Mach. Learn. Res., 2011)

Visualization of nonlinear kernel models in neuroimaging by sensitivity maps. - Peter Mondrup Rasmussen; Kristoffer Hougaard Madsen; Torben Ellegaard Lund; Lars Kai Hansen (NeuroImage, 2011)

Sparse non-linear denoising: Generalization performance and pattern reproducibility in functional MRI. - Trine Julie Abrahamsen; Lars Kai Hansen (Pattern Recognit. Lett., 2011)

Regularized Pre-image Estimation for Kernel PCA De-noising - Input Space Regularization and Sparse Reconstruction. - Trine Julie Abrahamsen; Lars Kai Hansen (J. Signal Process. Syst., 2011)

Simultaneous EEG Source and Forward Model Reconstruction (SOFOMORE) Using a Hierarchical Bayesian Approach. - Carsten Stahlhut; Morten Mørup; Ole Winther; Lars Kai Hansen (J. Signal Process. Syst., 2011)

Visualization of Nonlinear Classification Models in Neuroimaging - Signed Sensitivity Maps. - Peter Mondrup Rasmussen; Tanya Schmah; Kristoffer Hougaard Madsen; Torben Ellegaard Lund; Grigori Yourganov; Stephen C. Strother; Lars Kai Hansen (BIOSIGNALS, 2012)

A Hold-out method to correct PCA variance inflation. - Pablo Garcia-Moreno; Antonio Artés-Rodríguez; Lars Kai Hansen (CIP, 2012)

Attention: A machine learning perspective. - Lars Kai Hansen (CIP, 2012)

Detecting hierarchical structure in networks. - Tue Herlau; Morten Mørup; Mikkel N. Schmidt; Lars Kai Hansen (CIP, 2012)

Structured sparsity regularization approach to the EEG inverse problem. - Jair Montoya-Martínez; Antonio Artés-Rodríguez; Lars Kai Hansen; Massimiliano Pontil (CIP, 2012)

Cognitive semantic networks: Emotional verbs throw a tantrum but don't bite. - Michael Kai Petersen; Lars Kai Hansen (CIP, 2012)

An evaluation of EEG scanner's dependence on the imaging technique, forward model computation method, and array dimensionality. - Carsten Stahlhut; Hagai Thomas Attias; Arkadiusz Stopczynski; Michael Kai Petersen; Jakob Eg Larsen; Lars Kai Hansen (EMBC, 2012)

Identifying modular relations in complex brain networks. - Kasper Winther Andersen; Morten Mørup; Hartwig R. Siebner; Kristoffer Hougaard Madsen; Lars Kai Hansen (MLSP, 2012)

Modelling dense relational data. - Tue Herlau; Morten Mørup; Mikkel N. Schmidt; Lars Kai Hansen (MLSP, 2012)

Archetypal analysis for machine learning and data mining. - Morten Mørup; Lars Kai Hansen (Neurocomputing, 2012)

Nonlinear denoising and analysis of neuroimages with kernel principal component analysis and pre-image estimation. - Peter Mondrup Rasmussen; Trine Julie Abrahamsen; Kristoffer Hougaard Madsen; Lars Kai Hansen (NeuroImage, 2012)

Model sparsity and brain pattern interpretation of classification models in neuroimaging. - Peter Mondrup Rasmussen; Lars Kai Hansen; Kristoffer Hougaard Madsen; Nathan William Churchill; Stephen C. Strother (Pattern Recognit., 2012)

Model Selection for Gaussian Kernel PCA Denoising. - Kasper Winther Jørgensen; Lars Kai Hansen (IEEE Trans. Neural Networks Learn. Syst., 2012)

Adaptive Regularization in Neural Network Modeling. - Jan Larsen; Claus Svarer; Lars Nonboe Andersen; Lars Kai Hansen (Neural Networks: Tricks of the Trade (2nd ed.), 2012)

Mobile real-time EEG imaging Bayesian inference with sparse, temporally smooth source priors. - Lars Kai Hansen; Sofie Therese Hansen; Carsten Stahlhut (BCI, 2013)

Towards a universal representation for audio information retrieval and analysis. - Bjørn Sand Jensen; Rasmus Troelsgård; Jan Larsen; Lars Kai Hansen (ICASSP, 2013)

Spatio temporal media components for neurofeedback. - Camilla Birgitte Falk Jensen; Michael Kai Petersen; Jakob Eg Larsen; Arkadiusz Stopczynski; Carsten Stahlhut; Marieta Georgieva Ivanova; Tobias Andersen; Lars Kai Hansen (ICME Workshops, 2013)

A hierarchical Bayesian M/EEG imagingmethod correcting for incomplete spatio-temporal priors. - Carsten Stahlhut; Hagai Thomas Attias; Kensuke Sekihara; David P. Wipf; Lars Kai Hansen; Srikantan S. Nagarajan (ISBI, 2013)

Learning the solution sparsity of an ill-posed linear inverse problem with the Variational Garrote. - Michael Riis Andersen; Sofie Therese Hansen; Lars Kai Hansen (MLSP, 2013)

Sparse Source EEG Imaging with the Variational Garrote. - Sofie Therese Hansen; Carsten Stahlhut; Lars Kai Hansen (PRNI, 2013)

Expansion of the Variational Garrote to a Multiple Measurement Vectors Model. - Sofie Therese Hansen; Carsten Stahlhut; Lars Kai Hansen (SCAI, 2013)

Dimensionality reduction for click-through rate prediction: Dense versus sparse representation. - Bjarne Ørum Fruergaard; Toke Jansen Hansen; Lars Kai Hansen (CoRR, 2013)

The Smartphone Brain Scanner: A Mobile Real-time Neuroimaging System - Arkadiusz Stopczynski; Carsten Stahlhut; Jakob Eg Larsen; Michael Kai Petersen; Lars Kai Hansen (CoRR, 2013)

FindZebra: A search engine for rare diseases. - Radu Dragusin; Paula Petcu; Christina Lioma; Birger Larsen; Henrik Jørgensen; Ingemar J. Cox; Lars Kai Hansen; Peter Ingwersen; Ole Winther (Int. J. Medical Informatics, 2013)

Variance inflation in high dimensional Support Vector Machines. - Trine Julie Abrahamsen; Lars Kai Hansen (Pattern Recognit. Lett., 2013)

Kernel Multivariate Analysis Framework for Supervised Subspace Learning: A Tutorial on Linear and Kernel Multivariate Methods. - Jerónimo Arenas-García; Kaare Brandt Petersen; Gustavo Camps-Valls; Lars Kai Hansen (IEEE Signal Process. Mag., 2013)

Preface. - Lars Kai Hansen; Søren Holdt Jensen; Jan Larsen (CIP, 2014)

Fast sampling from a Hidden Markov Model posterior for large data. - Rasmus Bonnevie; Lars Kai Hansen (MLSP, 2014)

Compact web browsing profiles for click-through rate prediction. - Bjarne Ørum Fruergaard; Lars Kai Hansen (MLSP, 2014)

Bayesian Inference for Structured Spike and Slab Priors. - Michael Riis Andersen; Ole Winther; Lars Kai Hansen (NIPS, 2014)

EEG source reconstruction using sparse basis function representations. - Sofie Therese Hansen; Lars Kai Hansen (PRNI, 2014)

Bayesian correlated component analysis for inference of joint EEG activation. - Andreas Trier Poulsen; Simon Kamronn; Lucas C. Parra; Lars Kai Hansen (PRNI, 2014)

Privacy for Personal Neuroinformatics. - Arkadiusz Stopczynski; Dazza Greenwood; Lars Kai Hansen; Alex Pentland (CoRR, 2014)

A Topic Model Approach to Multi-Modal Similarity. - Rasmus Troelsgård; Bjørn Sand Jensen; Lars Kai Hansen (CoRR, 2014)

A regularized matrix factorization approach to induce structured sparse-low-rank solutions in the EEG inverse problem. - Jair Montoya-Martínez; Antonio Artés-Rodríguez; Massimiliano Pontil; Lars Kai Hansen (EURASIP J. Adv. Signal Process., 2014)

Non-parametric Bayesian graph models reveal community structure in resting state fMRI. - Kasper Winther Andersen; Kristoffer Hougaard Madsen; Hartwig Roman Siebner; Mikkel N. Schmidt; Morten Mørup; Lars Kai Hansen (NeuroImage, 2014)

Frontal alpha oscillations distinguish leaders from followers: Multivariate decoding of mutually interacting brains. - Ivana Konvalinka; Markus Bauer 003; Carsten Stahlhut; Lars Kai Hansen; Andreas Roepstorff; Chris D. Frith (NeuroImage, 2014)

Denoising by semi-supervised kernel PCA preimaging. - Toke Jansen Hansen; Trine Julie Abrahamsen; Lars Kai Hansen (Pattern Recognit. Lett., 2014)

EEG source reconstruction performance as a function of skull conductance contrast. - Sofie Therese Hansen; Lars Kai Hansen (ICASSP, 2015)

Testing Multimodal Integration Hypotheses with Application to Schizophrenia Data. - Martin C. Axelsen; Nikolaj Bak; Lars Kai Hansen (PRNI, 2015)

Fusing Simultaneous EEG and fMRI Using Functional and Anatomical Information. - Sofie Therese Hansen; Irene Winkler; Lars Kai Hansen; Klaus-Robert Müller; Sven Dähne (PRNI, 2015)

Multiview Bayesian Correlated Component Analysis. - Simon Kamronn; Andreas Trier Poulsen; Lars Kai Hansen (Neural Comput., 2015)

Multimodal Data Fusion [Scanning the Issue]. - Tülay Adali; Christian Jutten; Lars Kai Hansen (Proc. IEEE, 2015)

Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation. - Søren Hauberg; Oren Freifeld; Anders Boesen Lindbo Larsen; John W. Fisher III; Lars Kai Hansen (AISTATS, 2016)

A Locally Adaptive Normal Distribution. - Georgios Arvanitidis; Lars Kai Hansen; Søren Hauberg (NIPS, 2016)

Measuring engagement in a classroom: Synchronised neural recordings during a video presentation. - Andreas Trier Poulsen; Simon Kamronn; Jacek Dmochowski; Lucas C. Parra; Lars Kai Hansen (CoRR, 2016)

Towards end-to-end optimisation of functional image analysis pipelines. - Albert Vilamala; Kristoffer Hougaard Madsen; Lars Kai Hansen (CoRR, 2016)

Data-driven forward model inference for EEG brain imaging. - Sofie Therese Hansen; Søren Hauberg; Lars Kai Hansen (NeuroImage, 2016)

The Center for Integrated Molecular Brain Imaging (Cimbi) database. - 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; et al. (NeuroImage, 2016)

Maximum Likelihood Estimation of Riemannian Metrics from Euclidean Data. - Georgios Arvanitidis; Lars Kai Hansen; Søren Hauberg (GSI, 2017)

EEG source imaging assists decoding in a face recognition task. - Rasmus S. Andersen; Anders U. Eliasen; Nicolai Pedersen; Michael Riis Andersen; Sofie Therese Hansen; Lars Kai Hansen (ICASSP, 2017)

Deep convolutional neural networks for interpretable analysis of EEG sleep stage scoring. - Albert Vilamala; Kristoffer Hougaard Madsen; Lars Kai Hansen (MLSP, 2017)

Adaptive smoothing in fMRI data processing neural networks. - Albert Vilamala; Kristoffer Hougaard Madsen; Lars Kai Hansen (PRNI, 2017)

Bayesian Inference for Spatio-temporal Spike-and-Slab Priors. - Michael Riis Andersen; Aki Vehtari; Ole Winther; Lars Kai Hansen (J. Mach. Learn. Res., 2017)

Spatio-temporal reconstruction of brain dynamics from EEG with a Markov prior. - Sofie Therese Hansen; Lars Kai Hansen (NeuroImage, 2017)

Bayesian Structure Learning for Dynamic Brain Connectivity. - Michael Riis Andersen; Ole Winther; Lars Kai Hansen; Russell A. Poldrack; Oluwasanmi Koyejo (AISTATS, 2018)

Inferring Visual Semantic Similarity with Deep Learning and Wikidata: Introducing imagesim-353*. - Finn Årup Nielsen; Lars Kai Hansen (DL4KGS@ESWC, 2018)

Semi-Supervised Sleep-Stage Scoring Based on Single Channel EEG. - Andreas Muff Munk; Kristoffer Vinther Olesen; Sirin Wilhelmsen Gangstad; Lars Kai Hansen (ICASSP, 2018)

Evaluating Models of Dynamic Functional Connectivity Using Predictive Classification Accuracy. - Søren Føns Vind Nielsen; Yuri Levin-Schwartz; Diego Vidaurre; Tülay Adali; Vince D. Calhoun; Kristoffer Hougaard Madsen; Lars Kai Hansen; Morten Mørup (ICASSP, 2018)

Latent Space Oddity: on the Curvature of Deep Generative Models. - Georgios Arvanitidis; Lars Kai Hansen; Søren Hauberg (ICLR (Poster), 2018)

A Differential Privacy Workflow for Inference of Parameters in the Rasch Model. - Teresa Anna Steiner; David Enslev Nyrnberg; Lars Kai Hansen (MIDAS/PAP@PKDD/ECML, 2018)

Sequence Classification Using Third-Order Moments. - Rasmus Troelsgård; Lars Kai Hansen (Neural Comput., 2018)

The Dangers of Following Trends in Research: Sparsity and Other Examples of Hammers in Search of Nails. - Tülay Adali; H. Joel Trussell; Lars Kai Hansen; Vince D. Calhoun (Proc. IEEE, 2018)

Distributed Active Learning Strategies on Edge Computing. - Jia Qian; Sarada Prasad Gochhayat; Lars Kai Hansen (CSCloud/EdgeCom, 2019)

Phase transition in PCA with missing data: Reduced signal-to-noise ratio, not sample size! - Niels Bruun Ipsen; Lars Kai Hansen (ICML, 2019)

Combining embedding methods for a word intrusion task. - Finn Årup Nielsen; Lars Kai Hansen (KONVENS, 2019)

Unmixing Oscillatory Brain Activity by EEG Source Localization and Empirical Mode Decomposition. - Sofie Therese Hansen; Apit Hemakom; Mads Gylling Safeldt; Lærke Karen Krohne; Kristoffer Hougaard Madsen; Hartwig R. Siebner; Danilo P. Mandic; Lars Kai Hansen (Comput. Intell. Neurosci., 2019)

Single-Trial Decoding of Scalp EEG under Natural Conditions. - Greta Tuckute; Sofie Therese Hansen; Nicolai Pedersen; Dea Steenstrup; Lars Kai Hansen (Comput. Intell. Neurosci., 2019)

Aggregating explainability methods for neural networks stabilizes explanations. - Laura Rieger; Lars Kai Hansen (CoRR, 2019)

Probabilistic Decoupling of Labels in Classification. - Jeppe Nørregaard; Lars Kai Hansen (CoRR, 2019)

Active Learning Solution on Distributed Edge Computing. - Jia Qian; Sayantan Sengupta; Lars Kai Hansen (CoRR, 2019)

Interpretability in Intelligent Systems - A New Concept? - Lars Kai Hansen; Laura Rieger (Explainable AI, 2019)

The Complexity of Social Media Response: Statistical Evidence for One-dimensional Engagement Signal in Twitter. - Damian Konrad Kowalczyk; Lars Kai Hansen (ICAART (2), 2020)

Robustness analytics to data heterogeneity in edge computing. - Jia Qian; Lars Kai Hansen; Xenofon Fafoutis; Prayag Tiwari; Hari Mohan Pandey (Comput. Commun., 2020)

Towards Federated Learning: Robustness Analytics to Data Heterogeneity. - Jia Qian; Xenofon Fafoutis; Lars Kai Hansen (CoRR, 2020)

IROF: a low resource evaluation metric for explanation methods. - Laura Rieger; Lars Kai Hansen (CoRR, 2020)

Client Adaptation improves Federated Learning with Simulated Non-IID Clients. - Laura Rieger; Rasmus M. Th. Høegh; Lars Kai Hansen (CoRR, 2020)

A simple defense against adversarial attacks on heatmap explanations. - Laura Rieger; Lars Kai Hansen (CoRR, 2020)

What can we learn from gradients? - Jia Qian; Lars Kai Hansen (CoRR, 2020)

On the Limits to Multi-modal Popularity Prediction on Instagram: A New Robust, Efficient and Explainable Baseline. - Christoffer Riis; Damian Konrad Kowalczyk; Lars Kai Hansen (ICAART (2), 2021)

Spontaneous Symmetry Breaking in Data Visualization. - Cilie W. Feldager; Søren Hauberg; Lars Kai Hansen (ICANN (2), 2021)

Generalization by design: Shortcuts to Generalization in Deep Learning. - Petr Taborsky; Lars Kai Hansen (CoRR, 2021)

Topic Model Robustness to Automatic Speech Recognition Errors in Podcast Transcripts. - Raluca Alexandra Fetic; Mikkel Jordahn; Lucas Chaves Lima; Rasmus Arpe Fogh Egebæk; Martin Carsten Nielsen; Benjamin Biering; Lars Kai Hansen (CoRR, 2021)

Real-Time Decoding of Attentional States Using Closed-Loop EEG Neurofeedback. - Greta Tuckute; Sofie Therese Hansen; Troels Wesenberg Kjaer; Lars Kai Hansen (Neural Comput., 2021)

Modulation transfer functions for audiovisual speech. - Nicolai Pedersen; Torsten Dau; Lars Kai Hansen; Jens Hjortkjær (PLoS Comput. Biol., 2022)

Robustness of Visual Explanations to Common Data Augmentation Methods. - Lenka Tetková; Lars Kai Hansen (CVPR Workshops, 2023)

Concept-Based Explainability for an EEG Transformer Model. - Anders Gjølbye Madsen; William Theodor Lehn-Schiøler; Áshildur Jónsdóttir; Bergdís Arnardóttir; Lars Kai Hansen (MLSP, 2023)

On the role of model uncertainties in Bayesian optimisation. - Jonathan Foldager; Mikkel Jordahn; Lars Kai Hansen; Michael Riis Andersen (UAI, 2023)

Automatic proficiency scoring for early-stage writing. - Michael Riis Andersen; Kristine Kabel; Jesper Bremholm; Jeppe Bundsgaard; Lars Kai Hansen (Comput. Educ. Artif. Intell., 2023)

On the role of Model Uncertainties in Bayesian Optimization. - Jonathan Foldager; Mikkel Jordahn; Lars Kai Hansen; Michael Riis Andersen (CoRR, 2023)

Robustness of Visual Explanations to Common Data Augmentation. - Lenka Tetková; Lars Kai Hansen (CoRR, 2023)

On convex conceptual regions in deep network representations. - Lenka Tetková; Thea Brüsch; Teresa Karen Scheidt; Fabian Martin Mager; Rasmus Ørtoft Aagaard; Jonathan Foldager; Tommy Sonne Alstrøm; Lars Kai Hansen (CoRR, 2023)

Masked Autoencoders with Multi-Window Attention Are Better Audio Learners. - Sarthak Yadav; Sergios Theodoridis; Lars Kai Hansen; Zheng-Hua Tan (CoRR, 2023)

Masked Autoencoders with Multi-Window Local-Global Attention Are Better Audio Learners. - Sarthak Yadav; Sergios Theodoridis; Lars Kai Hansen; Zheng-Hua Tan (ICLR, 2024)

Convexity Based Pruning of Speech Representation Models. - Teresa Dorszewski; Lenka Tetková; Lars Kai Hansen (MLSP, 2024)

Speed: Scalable Preprocessing of EEG Data for Self-Supervised Learning. - Anders Gjølbye Madsen; Lina Skerath; William Theodor Lehn-Schiøler; Nicolas Langer; Lars Kai Hansen (MLSP, 2024)

Hubness Reduction Improves Sentence-BERT Semantic Spaces. - Beatrix Miranda Ginn Nielsen; Lars Kai Hansen (NLDL, 2024)

Knowledge Graphs for Empirical Concept Retrieval. - Lenka Tetková; Teresa Karen Scheidt; Maria Mandrup Fogh; Ellen Marie Gaunby Jørgensen; Finn Årup Nielsen; Lars Kai Hansen (xAI (1), 2024)

Challenges in explaining deep learning models for data with biological variation. - Lenka Tetková; Erik Schou Dreier; Robin Malm; Lars Kai Hansen (CoRR, 2024)

BiSSL: Bilevel Optimization for Self-Supervised Pre-Training and Fine-Tuning. - Gustav Wagner Zakarias; Lars Kai Hansen; Zheng-Hua Tan (CoRR, 2024)

Danoliteracy of Generative, Large Language Models. - Søren V. Holm; Lars Kai Hansen; Martin Carsten Nielsen (CoRR, 2024)

Using sequences of life-events to predict human lives. - Germans Savcisens; Tina Eliassi-Rad; Lars Kai Hansen; Laust Hvas Mortensen; Lau Lilleholt; Anna Rogers; Ingo Zettler; Sune Lehmann (Nat. Comput. Sci., 2024)

How Redundant Is the Transformer Stack in Speech Representation Models? - Teresa Dorszewski; Albert Kjøller Jacobsen; Lenka Tetková; Lars Kai Hansen (ICASSP, 2025)

Connecting Concept Convexity and Human-Machine Alignment in Deep Neural Networks. - Teresa Dorszewski; Lenka Tetková; Lorenz Linhardt; Lars Kai Hansen (NLDL, 2025)

From Colors to Classes: Emergence of Concepts in Vision Transformers. - Teresa Dorszewski; Lenka Tetková; Robert Jenssen; Lars Kai Hansen; Kristoffer Knutsen Wickstrøm (CoRR, 2025)

Minimizing False-Positive Attributions in Explanations of Non-Linear Models. - Anders Gjølbye Madsen; Stefan Haufe; Lars Kai Hansen (CoRR, 2025)