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Measuring with no tape

Publicaciones

Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval

Autores: Frederik Warburg, Martin Jørgensen, Javier Civera, Søren Hauberg
Publicado en: IEEE/CVF International Conference on Computer Vision (ICCV), 2021, ISBN 978-1-6654-2812-5
Editor: IEEE
DOI: 10.1109/iccv48922.2021.01194

Pulling back information geometry

Autores: Georgios Arvanitidis, Miguel González-Duque, Alison Pouplin, Dimitrios Kalatzis, Søren Hauberg
Publicado en: Artificial Intelligence and Statistics (AISTATS), 2022
Editor: Proceedings of Machine Learning Research

Hierarchical VAEs Know What They Don’t Know

Autores: Jakob D. Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe
Publicado en: International Conference on Machine Learning (ICML), 2021
Editor: Proceedings of Machine Learning Research

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

Autores: Cong Geng, Jia Wang, Zhiyong Gao, Jes Frellsen, Søren Hauberg
Publicado en: Advances in Neural Information Processing Systems (NeurIPS), 2021, ISBN 9781713845393
Editor: Curran Associates

Probabilistic Spatial Transformer Networks

Autores: Pola Schwöbel; Frederik Rahbæk Warburg; Martin Jørgensen; Kristoffer Hougaard Madsen; Søren Hauberg
Publicado en: Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence}, Edición 1, 2022
Editor: PMLR
DOI: 10.48550/arxiv.2004.03637

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

Autores: Federico Bergamin, Pierre-Alexandre Mattei, Jakob Drachmann Havtorn, Hugo Sénétaire, Hugo Schmutz, Lars Maaløe, Søren Hauberg, Jes Frellsen
Publicado en: Artificial Intelligence and Statistics (AISTATS), 2022
Editor: Proceedings of Machine Learning Research

Geometrically Enriched Latent Spaces

Autores: Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf
Publicado en: Artificial Intelligence and Statistics (AISTATS), 2021
Editor: Proceedings of Machine Learning Research

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

Autores: González-Duque, Miguel; Palm, Rasmus Berg; Hauberg, Søren; Risi, Sebastian
Publicado en: 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, Edición 1, 2022
Editor: IEEE
DOI: 10.1109/cog51982.2022.9893612

Adaptive Cholesky Gaussian Processes

Autores: Simon Bartels, Kristoffer Stensbo-Smidt, Pablo Moreno-Munoz, Wouter Boomsma, Jes Frellsen, Søren Hauberg
Publicado en: Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, 2023
Editor: PMLR

Learning Riemannian Manifolds for Geodesic Motion Skills

Autores: Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Rozo
Publicado en: Robotics: Science and Systems (R:SS), 2021
Editor: Robotics Proceedings
DOI: 10.15607/rss.2021.xvii.082

Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models

Autores: Mallasto, Anton; Hauberg, Søren; Feragen, Aasa
Publicado en: roceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics, Edición 4, 2019
Editor: Proceedings of Machine Learning Research

Fast and Robust Shortest Paths on Manifolds Learned from Data

Autores: Arvanitidis, Georgios; Hauberg, Søren; Hennig, Philipp; Schober, Michael
Publicado en: Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics, Edición 3, 2019
Editor: Proceedings of Machine Learning Research

Deep Diffeomorphic Transformer Networks

Autores: Nicki Skafte Detlefsen, Oren Freifeld, Soren Hauberg
Publicado en: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018, Página(s) 4403-4412, ISBN 978-1-5386-6420-9
Editor: IEEE
DOI: 10.1109/cvpr.2018.00463

Latent Space Oddity: on the Curvature of Deep Generative Models

Autores: G. Arvanitidis, L.K. Hansen and S. Hauberg
Publicado en: International Conference on Learning Representations (ICLR), 2018
Editor: International Conference on Learning Representations (ICLR)

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

Autores: Frederik Warburg, Søren Hauberg, Manuel López-Antequera, Pau Gargallo, Yubin Kuang, Javier Civera
Publicado en: Computer Vision and Pattern Recognition, 2020
Editor: IEEE

Explicit Disentanglement of Appearance and Perspective in Generative Models

Autores: Nicki Skafte Detlefsen, Søren Hauberg
Publicado en: NeurIPS, 2019
Editor: NeurIPS

Reliable training and estimation of variance networks

Autores: Detlefsen, Nicki S.; Jørgensen, Martin; Hauberg, Søren
Publicado en: Advances in Neural Information Processing Systems (NeurIPS), Edición 2, 2019
Editor: NeurIPS

Directional Statistics with the Spherical Normal Distribution

Autores: Søren Hauberg
Publicado en: International Conference on Information Fusion (FUSION), 2018
Editor: IEEE
DOI: 10.23919/icif.2018.8455242

Variational Autoencoders with Riemannian Brownian Motion Priors

Autores: Dimitris Kalatzis, David Eklund, Georgios Arvanitidis Søren Hauberg
Publicado en: International Conference on Machine Learning, 2020
Editor: PMLR

On the Geometry of Latent Variable Models

Autores: Søren Hauberg
Publicado en: 2018
Editor: Oberwolfach

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

Autores: Jeppe Thagaard, Søren Hauberg, Bert van der Vegt, Thomas Ebstrup, Johan D. Hansen, Anders B. Dahl
Publicado en: 23rd INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING & COMPUTER ASSISTED INTERVENTION, 2020
Editor: Springer

Benchmarking Generative Latent Variable Models for Speech

Autores: Jakob Drachmann Havtorn, Lasse Borgholt, Søren Hauberg, Jes Frellsen, Lars Maaløe
Publicado en: ICLR Workshop on Deep Generative Models for Highly Structured Data, 2022
Editor: OpenReview

Revisiting Active Sets for Gaussian Process Decoders

Autores: Pablo Moreno-Muñoz, Cilie Feldager, Søren Hauberg
Publicado en: Advances in Neural Information Processing Systems, 2022
Editor: Curran Associates, Inc.

Spontaneous Symmetry Breaking in Data Visualization

Autores: Cilie W. Feldager, Søren Hauberg, Lars Kai Hansen
Publicado en: ICANN, 2021, ISBN 978-3-030-86339-5
Editor: Springer
DOI: 10.1007/978-3-030-86340-1_35

Isometric Gaussian Process Latent Variable Model for Dissimilarity Data

Autores: Jørgensen, Martin; Hauberg, Søren
Publicado en: International Conference on Machine Learning, 2021
Editor: Proceedings of Machine Learning Research

Laplacian Autoencoders for Learning Stochastic Representations

Autores: Marco Miani, Frederik Warburg, Pablo Moreno-Muñoz, Nicki Skafte, Søren Hauberg
Publicado en: Advances in Neural Information Processing Systems, 2022
Editor: Curran Associates, Inc.

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

Autores: Andrea Vallone, Frederik Warburg, Hans Hansen, Søren Hauberg, Javier Civera
Publicado en: IEEE Robotics and Automation Letters, 2022, ISSN 2377-3766
Editor: IEEE
DOI: 10.1109/lra.2022.3187491

Learning meaningful representations of protein sequences

Autores: Nicki Skafte Detlefsen, Søren Hauberg, Wouter Boomsma
Publicado en: Nature Communications, 2022, ISSN 2041-1723
Editor: Nature Publishing Group
DOI: 10.1038/s41467-022-29443-w

Intrinsic Grassmann Averages for Online Linear Robust and Nonlinear Subspace Learning

Autores: Rudrasis Chakraborty, Liu Yang, Søren Hauberg, Baba C. Vemuri.
Publicado en: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020, ISSN 1939-3539
Editor: IEEE

Parallel QR factorization of block-tridiagonal matrices

Autores: Alfredo Buttari, Søren Hauberg, Costy Kodsi
Publicado en: SIAM Journal on Scientific Computing, 2019, ISSN 1064-8275
Editor: Society for Industrial and Applied Mathematics
DOI: 10.1137/19m1306166

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

Autores: S.A. Zahedi; C. Kodsi; Filippo Berto
Publicado en: Theoretical and Applied Fracture Mechanics, 2019, ISSN 0167-8442
Editor: 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

Autores: Costy Kodsi, Andrey P. Jivkov
Publicado en: SIAM Journal on Applied Mathematics, 2021, ISSN 0036-1399
Editor: 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)

Autores: Hauberg, Søren
Publicado en: Edición 1, 2019
Editor: arxiv.org

Geodesic Clustering in Deep Generative Models

Autores: Yang, Tao; Arvanitidis, Georgios; Fu, Dongmei; Li, Xiaogang; Hauberg, Søren
Publicado en: Edición 2, 2018
Editor: arxiv

Expected path length on random manifolds

Autores: David Eklund, Søren Hauberg
Publicado en: 2019
Editor: arXiv

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