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2020 – today
- 2024
[c57]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo:
Neural Contractive Dynamical Systems. ICLR 2024- [c56]Cong Geng, Tian Han, Peng-Tao Jiang, Hao Zhang, Jinwei Chen, Søren Hauberg, Bo Li:
Improving Adversarial Energy-Based Model via Diffusion Process. ICML 2024 - [c55]Andreas Plesner
, Hans Henrik Brandenborg Sørensen, Søren Hauberg:
Accurate Computation of the Logarithm of Modified Bessel Functions on GPUs. ICS 2024: 213-224 - [i51]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo:
Neural Contractive Dynamical Systems. CoRR abs/2401.09352 (2024) - [i50]Cong Geng, Tian Han, Peng-Tao Jiang, Hao Zhang, Jinwei Chen, Søren Hauberg, Bo Li:
Improving Adversarial Energy-Based Model via Diffusion Process. CoRR abs/2403.01666 (2024) - [i49]Richard Michael, Simon Bartels, Miguel González Duque, Yevgen Zainchkovskyy, Jes Frellsen, Søren Hauberg, Wouter Boomsma:
A Continuous Relaxation for Discrete Bayesian Optimization. CoRR abs/2404.17452 (2024) - [i48]Nicholas Krämer, Pablo Moreno-Muñoz, Hrittik Roy, Søren Hauberg:
Gradients of Functions of Large Matrices. CoRR abs/2405.17277 (2024) - [i47]Hrittik Roy, Marco Miani, Carl Henrik Ek, Philipp Hennig, Marvin Pförtner, Lukas Tatzel, Søren Hauberg:
Reparameterization invariance in approximate Bayesian inference. CoRR abs/2406.03334 (2024) - [i46]Miguel González Duque, Richard Michael, Simon Bartels, Yevgen Zainchkovskyy, Søren Hauberg, Wouter Boomsma:
A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences. CoRR abs/2406.04739 (2024) - [i45]Stas Syrota, Pablo Moreno-Muñoz, Søren Hauberg:
Decoder ensembling for learned latent geometries. CoRR abs/2408.07507 (2024) - 2023
- [j14]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Rozo:
Reactive motion generation on learned Riemannian manifolds. Int. J. Robotics Res. 42(10): 729-754 (2023) - [j13]Alison Pouplin, David Eklund, Carl Henrik Ek, Søren Hauberg:
Identifying latent distances with Finslerian geometry. Trans. Mach. Learn. Res. 2023 (2023) - [c54]Simon Bartels, Kristoffer Stensbo-Smidt, Pablo Moreno-Muñoz, Wouter Boomsma, Jes Frellsen, Søren Hauberg:
Adaptive Cholesky Gaussian Processes. AISTATS 2023: 408-452 - [c53]Thoranna Bender, Simon Møe Sørensen, Alireza Kashani, Kristjan Eldjarn Hjorleifsson, Grethe Hyldig, Søren Hauberg, Serge J. Belongie, Frederik Warburg:
Learning to Taste: A Multimodal Wine Dataset. NeurIPS 2023 - [c52]Federico Bergamin, Pablo Moreno-Muñoz, Søren Hauberg, Georgios Arvanitidis:
Riemannian Laplace approximations for Bayesian neural networks. NeurIPS 2023 - [c51]Pablo Moreno-Muñoz, Pol Garcia Recasens, Søren Hauberg:
On Masked Pre-training and the Marginal Likelihood. NeurIPS 2023 - [c50]Frederik Warburg, Marco Miani, Silas Brack, Søren Hauberg:
Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval. NeurIPS 2023 - [i44]Frederik Warburg, Marco Miani, Silas Brack, Søren Hauberg:
Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval. CoRR abs/2302.01332 (2023) - [i43]Kilian Zepf, Selma Wanna, Marco Miani, Juston Moore, Jes Frellsen, Søren Hauberg, Aasa Feragen, Frederik Warburg:
Laplacian Segmentation Networks: Improved Epistemic Uncertainty from Spatial Aleatoric Uncertainty. CoRR abs/2303.13123 (2023) - [i42]Pablo Moreno-Muñoz, Pol G. Recasens, Søren Hauberg:
On Masked Pre-training and the Marginal Likelihood. CoRR abs/2306.00520 (2023) - [i41]Federico Bergamin, Pablo Moreno-Muñoz, Søren Hauberg, Georgios Arvanitidis:
Riemannian Laplace approximations for Bayesian neural networks. CoRR abs/2306.07158 (2023) - [i40]Johan Ziruo Ye, Thomas Ørkild, Peter Lempel Søndergaard, Søren Hauberg:
Variational Point Encoding Deformation for Dental Modeling. CoRR abs/2307.10895 (2023) - [i39]Thoranna Bender, Simon Møe Sørensen, Alireza Kashani, Kristjan Eldjarn Hjorleifsson, Grethe Hyldig, Søren Hauberg, Serge J. Belongie, Frederik Warburg:
Learning to Taste: A Multimodal Wine Dataset. CoRR abs/2308.16900 (2023) - 2022
- [j12]Andrea Vallone, Frederik Warburg, Hans Hansen, Søren Hauberg, Javier Civera:
Danish Airs and Grounds: A Dataset for Aerial-to-Street-Level Place Recognition and Localization. IEEE Robotics Autom. Lett. 7(4): 9207-9215 (2022) - [c49]Georgios Arvanitidis, Miguel González Duque, Alison Pouplin, Dimitrios Kalatzis, Søren Hauberg:
Pulling back information geometry. AISTATS 2022: 4872-4894 - [c48]Federico Bergamin, Pierre-Alexandre Mattei, Jakob Drachmann Havtorn, Hugo Sénétaire, Hugo Schmutz, Lars Maaløe, Søren Hauberg, Jes Frellsen:
Model-agnostic out-of-distribution detection using combined statistical tests. AISTATS 2022: 10753-10776 - [c47]Miguel González Duque, Rasmus Berg Palm, Søren Hauberg, Sebastian Risi:
Mario Plays on a Manifold: Generating Functional Content in Latent Space through Differential Geometry. CoG 2022: 385-392 - [c46]Marco Miani, Frederik Warburg, Pablo Moreno-Muñoz, Nicki Skafte Detlefsen, Søren Hauberg:
Laplacian Autoencoders for Learning Stochastic Representations. NeurIPS 2022 - [c45]Pablo Moreno-Muñoz, Cilie W. Feldager, Søren Hauberg:
Revisiting Active Sets for Gaussian Process Decoders. NeurIPS 2022 - [c44]Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, Søren Hauberg, Dmitriy Nielsen, Stefan Sommer, David A. Klindt, Erik Hermansen, Melvin Vaupel, Benjamin A. Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe'er, Felix Ambellan, Martin Hanik, Esfandiar Nava-Yazdani, Christoph von Tycowicz, Nina Miolane:
ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results. TAG-ML 2022: 269-276 - [c43]Pola Schwöbel, Frederik Rahbæk Warburg, Martin Jørgensen, Kristoffer Hougaard Madsen, Søren Hauberg:
Probabilistic spatial transformer networks. UAI 2022: 1749-1759 - [i38]Pierre Segonne, Yevgen Zainchkovskyy, Søren Hauberg:
Robust uncertainty estimates with out-of-distribution pseudo-inputs training. CoRR abs/2201.05890 (2022) - [i37]Andrea Vallone, Frederik Warburg, Hans Hansen, Søren Hauberg, Javier Civera:
Danish Airs and Grounds: A Dataset for Aerial-to-Street-Level Place Recognition and Localization. CoRR abs/2202.01821 (2022) - [i36]Simon Bartels, Kristoffer Stensbo-Smidt, Pablo Moreno-Muñoz, Wouter Boomsma, Jes Frellsen, Søren Hauberg:
Adaptive Cholesky Gaussian Processes. CoRR abs/2202.10769 (2022) - [i35]Jakob D. Havtorn, Lasse Borgholt, Søren Hauberg, Jes Frellsen, Lars Maaløe:
Benchmarking Generative Latent Variable Models for Speech. CoRR abs/2202.12707 (2022) - [i34]Federico Bergamin, Pierre-Alexandre Mattei, Jakob D. Havtorn, Hugo Sénétaire, Hugo Schmutz, Lars Maaløe, Søren Hauberg, Jes Frellsen:
Model-agnostic out-of-distribution detection using combined statistical tests. CoRR abs/2203.01097 (2022) - [i33]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo:
Reactive Motion Generation on Learned Riemannian Manifolds. CoRR abs/2203.07761 (2022) - [i32]Andri Bergsson, Søren Hauberg:
Visualizing Riemannian data with Rie-SNE. CoRR abs/2203.09253 (2022) - [i31]Miguel González Duque, Rasmus Berg Palm, Søren Hauberg, Sebastian Risi:
Mario Plays on a Manifold: Generating Functional Content in Latent Space through Differential Geometry. CoRR abs/2206.00106 (2022) - [i30]Helene Hauschultz, Rasmus Berg Palm, Pablo Moreno-Muños, Nicki Skafte Detlefsen, Andrew Allan du Plessis, Søren Hauberg:
Is an encoder within reach? CoRR abs/2206.01552 (2022) - [i29]Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Umberto Lupo, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, Søren Hauberg, Dmitriy Nielsen, Stefan Sommer, David A. Klindt, Erik Hermansen, Melvin Vaupel, Benjamin A. Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe'er, Felix Ambellan, Martin Hanik, Esfandiar Nava-Yazdani, Christoph von Tycowicz, Nina Miolane:
ICLR 2022 Challenge for Computational Geometry and Topology: Design and Results. CoRR abs/2206.09048 (2022) - [i28]Marco Miani, Frederik Warburg, Pablo Moreno-Muñoz, Nicki Skafte Detlefsen, Søren Hauberg:
Laplacian Autoencoders for Learning Stochastic Representations. CoRR abs/2206.15078 (2022) - [i27]Pablo Moreno-Muñoz, Cilie W. Feldager, Søren Hauberg:
Revisiting Active Sets for Gaussian Process Decoders. CoRR abs/2209.04636 (2022) - [i26]Yevgen Zainchkovskyy, Jesper Ferkinghoff-Borg, Anja Bennett, Thomas Egebjerg, Nikolai Lorenzen, Per Greisen Jr., Søren Hauberg, Carsten Stahlhut:
Probabilistic thermal stability prediction through sparsity promoting transformer representation. CoRR abs/2211.05698 (2022) - [i25]Alison Pouplin, David Eklund, Carl Henrik Ek, Søren Hauberg:
Identifying latent distances with Finslerian geometry. CoRR abs/2212.10010 (2022) - 2021
- [j11]Rudrasis Chakraborty, Liu Yang, Søren Hauberg, Baba C. Vemuri:
Intrinsic Grassmann Averages for Online Linear, Robust and Nonlinear Subspace Learning. IEEE Trans. Pattern Anal. Mach. Intell. 43(11): 3904-3917 (2021) - [c42]Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf:
Geometrically Enriched Latent Spaces. AISTATS 2021: 631-639 - [c41]Cilie W. Feldager, Søren Hauberg, Lars Kai Hansen:
Spontaneous Symmetry Breaking in Data Visualization. ICANN (2) 2021: 435-446 - [c40]Frederik Warburg, Martin Jørgensen, Javier Civera, Søren Hauberg:
Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval. ICCV 2021: 12138-12148 - [c39]Jakob Drachmann Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe:
Hierarchical VAEs Know What They Don't Know. ICML 2021: 4117-4128 - [c38]Martin Jørgensen, Søren Hauberg:
Isometric Gaussian Process Latent Variable Model for Dissimilarity Data. ICML 2021: 5127-5136 - [c37]Cong Geng, Jia Wang, Zhiyong Gao, Jes Frellsen, Søren Hauberg:
Bounds all around: training energy-based models with bidirectional bounds. NeurIPS 2021: 19808-19821 - [c36]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo:
Learning Riemannian Manifolds for Geodesic Motion Skills. Robotics: Science and Systems 2021 - [i24]Jakob D. Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe:
Hierarchical VAEs Know What They Don't Know. CoRR abs/2102.08248 (2021) - [i23]Dimitris Kalatzis, Johan Ziruo Ye, Jesper Wohlert, Søren Hauberg:
Multi-chart flows. CoRR abs/2106.03500 (2021) - [i22]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo:
Learning Riemannian Manifolds for Geodesic Motion Skills. CoRR abs/2106.04315 (2021) - [i21]Georgios Arvanitidis, Miguel González Duque, Alison Pouplin, Dimitris Kalatzis, Søren Hauberg:
Pulling back information geometry. CoRR abs/2106.05367 (2021) - [i20]Cong Geng, Jia Wang, Zhiyong Gao, Jes Frellsen, Søren Hauberg:
Bounds all around: training energy-based models with bidirectional bounds. CoRR abs/2111.00929 (2021) - 2020
- [j10]Alfredo Buttari, Søren Hauberg, Costy Kodsi:
Parallel QR Factorization of Block-Tridiagonal Matrices. SIAM J. Sci. Comput. 42(6): C313-C334 (2020) - [c35]Frederik Warburg, Søren Hauberg, Manuel López-Antequera, Pau Gargallo, Yubin Kuang, Javier Civera:
Mapillary Street-Level Sequences: A Dataset for Lifelong Place Recognition. CVPR 2020: 2623-2632 - [c34]Dimitrios Kalatzis, David Eklund, Georgios Arvanitidis, Søren Hauberg:
Variational Autoencoders with Riemannian Brownian Motion Priors. ICML 2020: 5053-5066 - [c33]Jeppe Thagaard, Søren Hauberg, Bert van der Vegt, Thomas Ebstrup, Johan D. Hansen, Anders B. Dahl:
Can You Trust Predictive Uncertainty Under Real Dataset Shifts in Digital Pathology? MICCAI (1) 2020: 824-833 - [i19]Dimitris Kalatzis, David Eklund, Georgios Arvanitidis, Søren Hauberg:
Variational Autoencoders with Riemannian Brownian Motion Priors. CoRR abs/2002.05227 (2020) - [i18]Pola Schwöbel, Frederik Warburg, Martin Jørgensen, Kristoffer H. Madsen, Søren Hauberg:
Probabilistic Spatial Transformers for Bayesian Data Augmentation. CoRR abs/2004.03637 (2020) - [i17]Martin Jørgensen, Søren Hauberg:
Isometric Gaussian Process Latent Variable Model for Dissimilarity Data. CoRR abs/2006.11741 (2020) - [i16]Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf:
Geometrically Enriched Latent Spaces. CoRR abs/2008.00565 (2020) - [i15]Martin Jørgensen, Søren Hauberg:
Reparametrization Invariance in non-parametric Causal Discovery. CoRR abs/2008.05552 (2020) - [i14]Frederik Warburg, Martin Jørgensen, Javier Civera, Søren Hauberg:
Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval. CoRR abs/2011.12663 (2020) - [i13]Nicki Skafte Detlefsen, Søren Hauberg, Wouter Boomsma:
What is a meaningful representation of protein sequences? CoRR abs/2012.02679 (2020)
2010 – 2019
- 2019
- [c32]Georgios Arvanitidis, Søren Hauberg, Philipp Hennig, Michael Schober:
Fast and Robust Shortest Paths on Manifolds Learned from Data. AISTATS 2019: 1506-1515 - [c31]Anton Mallasto, Søren Hauberg, Aasa Feragen:
Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models. AISTATS 2019: 2368-2377 - [c30]Nicki Skafte Detlefsen, Søren Hauberg:
Explicit Disentanglement of Appearance and Perspective in Generative Models. NeurIPS 2019: 1016-1026 - [c29]Nicki Skafte Detlefsen, Martin Jørgensen, Søren Hauberg:
Reliable training and estimation of variance networks. NeurIPS 2019: 6323-6333 - [i12]Georgios Arvanitidis, Søren Hauberg, Philipp Hennig, Michael Schober:
Fast and Robust Shortest Paths on Manifolds Learned from Data. CoRR abs/1901.07229 (2019) - [i11]Nicki Skafte Detlefsen, Martin Jørgensen, Søren Hauberg:
Reliable training and estimation of variance networks. CoRR abs/1906.03260 (2019) - [i10]Nicki Skafte Detlefsen, Søren Hauberg:
Explicit Disentanglement of Appearance and Perspective in Generative Models. CoRR abs/1906.11881 (2019) - [i9]David Eklund, Søren Hauberg:
Expected path length on random manifolds. CoRR abs/1908.07377 (2019) - 2018
- [c28]Nicki Skafte Detlefsen, Oren Freifeld, Søren Hauberg:
Deep Diffeomorphic Transformer Networks. CVPR 2018: 4403-4412 - [c27]Søren Hauberg:
Directional Statistics with the Spherical Normal Distribution. FUSION 2018: 704-711 - [c26]Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg:
Latent Space Oddity: on the Curvature of Deep Generative Models. ICLR (Poster) 2018 - [i8]Anton Mallasto, Søren Hauberg, Aasa Feragen:
Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models. CoRR abs/1805.09122 (2018) - [i7]Søren Hauberg:
Only Bayes should learn a manifold (on the estimation of differential geometric structure from data). CoRR abs/1806.04994 (2018) - [i6]Tao Yang, Georgios Arvanitidis, Dongmei Fu, Xiaogang Li, Søren Hauberg:
Geodesic Clustering in Deep Generative Models. CoRR abs/1809.04747 (2018) - 2017
- [j9]Oren Freifeld, Søren Hauberg, Kayhan Batmanghelich, John W. Fisher III:
Transformations Based on Continuous Piecewise-Affine Velocity Fields. IEEE Trans. Pattern Anal. Mach. Intell. 39(12): 2496-2509 (2017) - [c25]Rudrasis Chakraborty, Søren Hauberg, Baba C. Vemuri:
Intrinsic Grassmann Averages for Online Linear and Robust Subspace Learning. CVPR 2017: 801-809 - [c24]Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg:
Maximum Likelihood Estimation of Riemannian Metrics from Euclidean Data. GSI 2017: 38-46 - [i5]Rudrasis Chakraborty, Søren Hauberg, Baba C. Vemuri:
Intrinsic Grassmann Averages for Online Linear and Robust Subspace Learning. CoRR abs/1702.01005 (2017) - 2016
- [j8]Sofie Therese Hansen, Søren Hauberg, Lars Kai Hansen:
Data-driven forward model inference for EEG brain imaging. NeuroImage 139: 249-258 (2016) - [j7]Søren Hauberg:
Principal Curves on Riemannian Manifolds. IEEE Trans. Pattern Anal. Mach. Intell. 38(9): 1915-1921 (2016) - [j6]Søren Hauberg, Aasa Feragen, Raffi Enficiaud, Michael J. Black:
Scalable Robust Principal Component Analysis Using Grassmann Averages. IEEE Trans. Pattern Anal. Mach. Intell. 38(11): 2298-2311 (2016) - [c23]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 - [c22]Aasa Feragen, Søren Hauberg:
Open Problem: Kernel methods on manifolds and metric spaces. What is the probability of a positive definite geodesic exponential kernel? COLT 2016: 1647-1650 - [c21]Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg:
A Locally Adaptive Normal Distribution. NIPS 2016: 4251-4259 - 2015
- [c20]Aasa Feragen, François Lauze, Søren Hauberg:
Geodesic exponential kernels: When curvature and linearity conflict. CVPR 2015: 3032-3042 - [c19]Oren Freifeld, Søren Hauberg, Kayhan N. Batmanghelich, John W. Fisher III:
Highly-Expressive Spaces of Well-Behaved Transformations: Keeping it Simple. ICCV 2015: 2911-2919 - [c18]Søren Hauberg, Michael Schober, Matthew G. Liptrot, Philipp Hennig, Aasa Feragen:
A Random Riemannian Metric for Probabilistic Shortest-Path Tractography. MICCAI (1) 2015: 597-604 - [i4]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
- [c17]Philipp Hennig, Søren Hauberg:
Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics. AISTATS 2014: 347-355 - [c16]Oren Freifeld, Søren Hauberg, Michael J. Black:
Model Transport: Towards Scalable Transfer Learning on Manifolds. CVPR 2014: 1378-1385 - [c15]Søren Hauberg, Aasa Feragen, Michael J. Black:
Grassmann Averages for Scalable Robust PCA. CVPR 2014: 3810-3817 - [c14]Michael Schober, Niklas Kasenburg, Aasa Feragen, Philipp Hennig, Søren Hauberg:
Probabilistic Shortest Path Tractography in DTI Using Gaussian Process ODE Solvers. MICCAI (3) 2014: 265-272 - [c13]Alessandra Tosi, Søren Hauberg, Alfredo Vellido, Neil D. Lawrence:
Metrics for Probabilistic Geometries. UAI 2014: 800-808 - [i3]Aasa Feragen, François Lauze, Søren Hauberg:
Geodesic Exponential Kernels: When Curvature and Linearity Conflict. CoRR abs/1411.0296 (2014) - [i2]Alessandra Tosi, Søren Hauberg, Alfredo Vellido, Neil D. Lawrence:
Metrics for Probabilistic Geometries. CoRR abs/1411.7432 (2014) - 2013
- [j5]Søren Hauberg, François Lauze, Kim Steenstrup Pedersen:
Unscented Kalman Filtering on Riemannian Manifolds. J. Math. Imaging Vis. 46(1): 103-120 (2013) - [i1]Philipp Hennig, Søren Hauberg:
Probabilistic Numerical Analysis in Riemannian Statistics. CoRR abs/1306.0308 (2013) - 2012
- [j4]Søren Hauberg, Stefan Sommer, Kim Steenstrup Pedersen:
Natural metrics and least-committed priors for articulated tracking. Image Vis. Comput. 30(6-7): 453-461 (2012) - [c12]Søren Hauberg, Kim Steenstrup Pedersen:
Spatial Measures between Human Poses for Classification and Understanding. AMDO 2012: 26-36 - [c11]Søren Hauberg, Oren Freifeld, Michael J. Black:
A Geometric take on Metric Learning. NIPS 2012: 2033-2041 - 2011
- [j3]Søren Hauberg, Kim Steenstrup Pedersen:
Predicting Articulated Human Motion from Spatial Processes. Int. J. Comput. Vis. 94(3): 317-334 (2011) - [c10]Søren Hauberg, Kim Steenstrup Pedersen:
Data-Driven Importance Distributions for Articulated Tracking. EMMCVPR 2011: 287-299 - [c9]Peter Mysling, Søren Hauberg, Kim Steenstrup Pedersen:
An Empirical Study on the Performance of Spectral Manifold Learning Techniques. ICANN (1) 2011: 347-354 - [c8]Aasa Feragen, Søren Hauberg, Mads Nielsen, François Lauze:
Means in spaces of tree-like shapes. ICCV 2011: 736-746 - [c7]Anders Boesen Lindbo Larsen, Søren Hauberg, Kim Steenstrup Pedersen:
Unscented Kalman Filtering for Articulated Human Tracking. SCIA 2011: 228-237 - 2010
- [c6]Søren Hauberg, Kim Steenstrup Pedersen:
Stick It! Articulated Tracking Using Spatial Rigid Object Priors. ACCV (3) 2010: 758-769 - [c5]Stefan Sommer, François Lauze, Søren Hauberg, Mads Nielsen:
Manifold Valued Statistics, Exact Principal Geodesic Analysis and the Effect of Linear Approximations. ECCV (6) 2010: 43-56 - [c4]Rune Møllegaard Friborg, Søren Hauberg, Kenny Erleben:
GPU Accelerated Likelihoods for Stereo-Based Articulated Tracking. ECCV Workshops (1) 2010: 359-371 - [c3]Søren Hauberg, Stefan Sommer, Kim Steenstrup Pedersen:
Gaussian-Like Spatial Priors for Articulated Tracking. ECCV (1) 2010: 425-437
2000 – 2009
- 2009
- [c2]Søren Hauberg, Jérôe Lapuyade, Morten Engell-Nørregård, Kenny Erleben, Kim Steenstrup Pedersen:
Three Dimensional Monocular Human Motion Analysis in End-Effector Space. EMMCVPR 2009: 235-248 - [c1]Morten Engell-Nørregård, Søren Hauberg, Jérôe Lapuyade, Kenny Erleben, Kim Steenstrup Pedersen:
Interactive Inverse Kinematics for Human Motion Estimation. VRIPHYS 2009: 77-84 - 2008
- [j2]Søren Hauberg, Jakob Sloth:
An Efficient Algorithm for Modelling Duration in Hidden Markov Models, with a Dramatic Application. J. Math. Imaging Vis. 31(2-3): 165-170 (2008) - [j1]