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Lars 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 - [i41]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) - [i40]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) - [i39]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) - [i38]Teresa Dorszewski, Lenka Tetková, Lars Kai Hansen:
Convexity-based Pruning of Speech Representation Models. CoRR abs/2408.11858 (2024) - [i37]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) - [i36]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) - 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]