Measuring with no tape

Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval

Author(s): Frederik Warburg, Martin Jørgensen, Javier Civera, Søren Hauberg
Published in: IEEE/CVF International Conference on Computer Vision (ICCV), 2021, ISBN 978-1-6654-2812-5
Publisher: IEEE
DOI: 10.1109/iccv48922.2021.01194

Pulling back information geometry

Author(s): Georgios Arvanitidis, Miguel González-Duque, Alison Pouplin, Dimitrios Kalatzis, Søren Hauberg
Published in: Artificial Intelligence and Statistics (AISTATS), 2022
Publisher: Proceedings of Machine Learning Research

Hierarchical VAEs Know What They Don’t Know

Author(s): Jakob D. Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe
Published in: International Conference on Machine Learning (ICML), 2021
Publisher: Proceedings of Machine Learning Research

Bounds all around: training energy-based models with bidirectional bounds

Author(s): Cong Geng, Jia Wang, Zhiyong Gao, Jes Frellsen, Søren Hauberg
Published in: Advances in Neural Information Processing Systems (NeurIPS), 2021, ISBN 9781713845393
Publisher: Curran Associates

Probabilistic Spatial Transformer Networks

Author(s): Pola Schwöbel; Frederik Rahbæk Warburg; Martin Jørgensen; Kristoffer Hougaard Madsen; Søren Hauberg
Published in: Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence}, Issue 1, 2022
Publisher: PMLR
DOI: 10.48550/arxiv.2004.03637

Model-agnostic out-of-distribution detection using combined statistical tests

Author(s): Federico Bergamin, Pierre-Alexandre Mattei, Jakob Drachmann Havtorn, Hugo Sénétaire, Hugo Schmutz, Lars Maaløe, Søren Hauberg, Jes Frellsen
Published in: Artificial Intelligence and Statistics (AISTATS), 2022
Publisher: Proceedings of Machine Learning Research

Geometrically Enriched Latent Spaces

Author(s): Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf
Published in: Artificial Intelligence and Statistics (AISTATS), 2021
Publisher: Proceedings of Machine Learning Research

Mario Plays on a Manifold: Generating Functional Content in Latent Space through Differential Geometry

Author(s): González-Duque, Miguel; Palm, Rasmus Berg; Hauberg, Søren; Risi, Sebastian
Published in: Gonzalez-Duque , M , Palm , R B , Hauberg , S & Risi , S 2022 , Mario Plays on a Manifold: Generating Functional Content in Latent Space through Differential Geometry . in Proceedings of 2022 IEEE Conference on Games . IEEE , 2022 IEEE Conference on Games , Beijing , China , 21/08/2022 . https://doi.org/10.1109/CoG51982.2022.9893612, Issue 1, 2022
Publisher: IEEE
DOI: 10.1109/cog51982.2022.9893612

Adaptive Cholesky Gaussian Processes

Author(s): Simon Bartels, Kristoffer Stensbo-Smidt, Pablo Moreno-Munoz, Wouter Boomsma, Jes Frellsen, Søren Hauberg
Published in: Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, 2023
Publisher: PMLR

Learning Riemannian Manifolds for Geodesic Motion Skills

Author(s): Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Rozo
Published in: Robotics: Science and Systems (R:SS), 2021
Publisher: Robotics Proceedings
DOI: 10.15607/rss.2021.xvii.082

Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models

Author(s): Mallasto, Anton; Hauberg, Søren; Feragen, Aasa
Published in: roceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics, Issue 4, 2019
Publisher: Proceedings of Machine Learning Research

Fast and Robust Shortest Paths on Manifolds Learned from Data

Author(s): Arvanitidis, Georgios; Hauberg, Søren; Hennig, Philipp; Schober, Michael
Published in: Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics, Issue 3, 2019
Publisher: Proceedings of Machine Learning Research

Deep Diffeomorphic Transformer Networks

Author(s): Nicki Skafte Detlefsen, Oren Freifeld, Soren Hauberg
Published in: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018, Page(s) 4403-4412, ISBN 978-1-5386-6420-9
Publisher: IEEE
DOI: 10.1109/cvpr.2018.00463

Latent Space Oddity: on the Curvature of Deep Generative Models

Author(s): G. Arvanitidis, L.K. Hansen and S. Hauberg
Published in: International Conference on Learning Representations (ICLR), 2018
Publisher: International Conference on Learning Representations (ICLR)

Mapillary Street-Level Sequences: A Dataset for Lifelong Place Recognition

Author(s): Frederik Warburg, Søren Hauberg, Manuel López-Antequera, Pau Gargallo, Yubin Kuang, Javier Civera
Published in: Computer Vision and Pattern Recognition, 2020
Publisher: IEEE

Explicit Disentanglement of Appearance and Perspective in Generative Models

Author(s): Nicki Skafte Detlefsen, Søren Hauberg
Published in: NeurIPS, 2019
Publisher: NeurIPS

Reliable training and estimation of variance networks

Author(s): Detlefsen, Nicki S.; Jørgensen, Martin; Hauberg, Søren
Published in: Advances in Neural Information Processing Systems (NeurIPS), Issue 2, 2019
Publisher: NeurIPS

Directional Statistics with the Spherical Normal Distribution

Author(s): Søren Hauberg
Published in: International Conference on Information Fusion (FUSION), 2018
Publisher: IEEE
DOI: 10.23919/icif.2018.8455242

Variational Autoencoders with Riemannian Brownian Motion Priors

Author(s): Dimitris Kalatzis, David Eklund, Georgios Arvanitidis Søren Hauberg
Published in: International Conference on Machine Learning, 2020
Publisher: PMLR

On the Geometry of Latent Variable Models

Author(s): Søren Hauberg
Published in: 2018
Publisher: Oberwolfach

Can you trust predictive uncertainty under real dataset shifts in digital pathology?

Author(s): Jeppe Thagaard, Søren Hauberg, Bert van der Vegt, Thomas Ebstrup, Johan D. Hansen, Anders B. Dahl
Published in: 23rd INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING & COMPUTER ASSISTED INTERVENTION, 2020
Publisher: Springer

Benchmarking Generative Latent Variable Models for Speech

Author(s): Jakob Drachmann Havtorn, Lasse Borgholt, Søren Hauberg, Jes Frellsen, Lars Maaløe
Published in: ICLR Workshop on Deep Generative Models for Highly Structured Data, 2022
Publisher: OpenReview

Revisiting Active Sets for Gaussian Process Decoders

Author(s): Pablo Moreno-Muñoz, Cilie Feldager, Søren Hauberg
Published in: Advances in Neural Information Processing Systems, 2022
Publisher: Curran Associates, Inc.

Spontaneous Symmetry Breaking in Data Visualization

Author(s): Cilie W. Feldager, Søren Hauberg, Lars Kai Hansen
Published in: ICANN, 2021, ISBN 978-3-030-86339-5
Publisher: Springer
DOI: 10.1007/978-3-030-86340-1_35

Isometric Gaussian Process Latent Variable Model for Dissimilarity Data

Author(s): Jørgensen, Martin; Hauberg, Søren
Published in: International Conference on Machine Learning, 2021
Publisher: Proceedings of Machine Learning Research

Laplacian Autoencoders for Learning Stochastic Representations

Author(s): Marco Miani, Frederik Warburg, Pablo Moreno-Muñoz, Nicki Skafte, Søren Hauberg
Published in: Advances in Neural Information Processing Systems, 2022
Publisher: Curran Associates, Inc.

Danish Airs and Grounds: A Dataset for Aerial-to-Street-Level Place Recognition and Localization

Author(s): Andrea Vallone, Frederik Warburg, Hans Hansen, Søren Hauberg, Javier Civera
Published in: IEEE Robotics and Automation Letters, 2022, ISSN 2377-3766
Publisher: IEEE
DOI: 10.1109/lra.2022.3187491

Learning meaningful representations of protein sequences

Author(s): Nicki Skafte Detlefsen, Søren Hauberg, Wouter Boomsma
Published in: Nature Communications, 2022, ISSN 2041-1723
Publisher: Nature Publishing Group
DOI: 10.1038/s41467-022-29443-w

Intrinsic Grassmann Averages for Online Linear Robust and Nonlinear Subspace Learning

Author(s): Rudrasis Chakraborty, Liu Yang, Søren Hauberg, Baba C. Vemuri.
Published in: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020, ISSN 1939-3539
Publisher: IEEE

Parallel QR factorization of block-tridiagonal matrices

Author(s): Alfredo Buttari, Søren Hauberg, Costy Kodsi
Published in: SIAM Journal on Scientific Computing, 2019, ISSN 1064-8275
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/19m1306166

Numerical predictions of U-notched sample failure based on a discrete energy argument

Author(s): S.A. Zahedi; C. Kodsi; Filippo Berto
Published in: Theoretical and Applied Fracture Mechanics, 2019, ISSN 0167-8442
Publisher: Elsevier BV
DOI: 10.1016/j.tafmec.2018.12.014

Boundary Value Problem on a Weighted Graph Relevant to the Static Analysis of Truss Structures

Author(s): Costy Kodsi, Andrey P. Jivkov
Published in: SIAM Journal on Applied Mathematics, 2021, ISSN 0036-1399
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/18m1206977

Only Bayes should learn a manifold (on the estimation of differential geometric structure from data)

Author(s): Hauberg, Søren
Published in: Issue 1, 2019
Publisher: arxiv.org

Geodesic Clustering in Deep Generative Models

Author(s): Yang, Tao; Arvanitidis, Georgios; Fu, Dongmei; Li, Xiaogang; Hauberg, Søren
Published in: Issue 2, 2018
Publisher: arxiv

Expected path length on random manifolds

Author(s): David Eklund, Søren Hauberg
Published in: 2019
Publisher: arXiv

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