Hansen, Lars Kai

22 publications

TMLR 2026 BiSSL: Enhancing the Alignment Between Self-Supervised Pretraining and Downstream Fine-Tuning via Bilevel Optimization Gustav Wagner Zakarias, Lars Kai Hansen, Zheng-Hua Tan

NeurIPS 2025 Minimizing False-Positive Attributions in Explanations of Non-Linear Models Anders Gjølbye, Stefan Haufe, Lars Kai Hansen

NeurIPSW 2024 It's All Relative: Relative Uncertainty in Latent Spaces Using Relative Representations Fabian Mager, Valentino Maiorca, Lars Kai Hansen

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

ICLRW 2024 On Convex Decision Regions in Deep Network Representations Lenka Tětková, Thea Brüsch, Teresa Scheidt, Fabian Mager, Rasmus Aagaard, Jonathan Foldager, Tommy Sonne Alstrøm, Lars Kai Hansen

CVPRW 2023 Robustness of Visual Explanations to Common Data Augmentation Methods Lenka Tetková, Lars Kai Hansen

NeurIPSW 2023 Universality of Intrinsic Dimension of Latent Representations Across Models Teresa Scheidt, Lars Kai Hansen

ICML 2019 Phase Transition in PCA with Missing Data: Reduced Signal-to-Noise Ratio, Not Sample Size! Niels Ipsen, Lars Kai Hansen

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

ICLR 2018 Latent Space Oddity: On the Curvature of Deep Generative Models Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg

JMLR 2017 Bayesian Inference for Spatio-Temporal Spike-and-Slab Priors Michael Riis Andersen, Aki Vehtari, Ole Winther, Lars Kai Hansen

AISTATS 2016 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

JMLR 2011 A Cure for Variance Inflation in High Dimensional Kernel Principal Component Analysis Trine Julie Abrahamsen, Lars Kai Hansen

JMLR 2006 Linear State-Space Models for Blind Source Separation Rasmus Kongsgaard Olsson, Lars Kai Hansen

NeCo 2002 Mean-Field Approaches to Independent Component Analysis Pedro A. d. F. R. Højen-Sørensen, Ole Winther, Lars Kai Hansen

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

NeurIPS 2000 Generalizable Singular Value Decomposition for Ill-Posed Datasets Ulrik Kjems, Lars Kai Hansen, Stephen C. Strother

NeurIPS 1999 Bayesian Averaging Is Well-Temperated Lars Kai Hansen

NeurIPS 1999 Bayesian Modelling of fMRI Lime Series Pedro A. d. F. R. Højen-Sørensen, Lars Kai Hansen, Carl Edward Rasmussen

NeurIPS 1995 Pruning with Generalization Based Weight Saliencies: λOBD, λOBS Morten With Pedersen, Lars Kai Hansen, Jan Larsen

NeCo 1994 Pruning from Adaptive Regularization Lars Kai Hansen, Carl Edward Rasmussen

NeurIPS 1994 Recurrent Networks: Second Order Properties and Pruning Morten With Pedersen, Lars Kai Hansen