Measuring with no tape

Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval

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

Pulling back information geometry

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

Hierarchical VAEs Know What They Don’t Know

Autori: Jakob D. Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe
Pubblicato in: International Conference on Machine Learning (ICML), 2021
Editore: Proceedings of Machine Learning Research

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

Autori: Cong Geng, Jia Wang, Zhiyong Gao, Jes Frellsen, Søren Hauberg
Pubblicato in: Advances in Neural Information Processing Systems (NeurIPS), 2021, ISBN 9781713845393
Editore: Curran Associates

Probabilistic Spatial Transformer Networks

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

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

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

Geometrically Enriched Latent Spaces

Autori: Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf
Pubblicato in: Artificial Intelligence and Statistics (AISTATS), 2021
Editore: Proceedings of Machine Learning Research

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

Autori: González-Duque, Miguel; Palm, Rasmus Berg; Hauberg, Søren; Risi, Sebastian
Pubblicato 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, Numero 1, 2022
Editore: IEEE
DOI: 10.1109/cog51982.2022.9893612

Adaptive Cholesky Gaussian Processes

Autori: Simon Bartels, Kristoffer Stensbo-Smidt, Pablo Moreno-Munoz, Wouter Boomsma, Jes Frellsen, Søren Hauberg
Pubblicato in: Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, 2023
Editore: PMLR

Learning Riemannian Manifolds for Geodesic Motion Skills

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

Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models

Autori: Mallasto, Anton; Hauberg, Søren; Feragen, Aasa
Pubblicato in: roceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics, Numero 4, 2019
Editore: Proceedings of Machine Learning Research

Fast and Robust Shortest Paths on Manifolds Learned from Data

Autori: Arvanitidis, Georgios; Hauberg, Søren; Hennig, Philipp; Schober, Michael
Pubblicato in: Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics, Numero 3, 2019
Editore: Proceedings of Machine Learning Research

Deep Diffeomorphic Transformer Networks

Autori: Nicki Skafte Detlefsen, Oren Freifeld, Soren Hauberg
Pubblicato in: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018, Pagina/e 4403-4412, ISBN 978-1-5386-6420-9
Editore: IEEE
DOI: 10.1109/cvpr.2018.00463

Latent Space Oddity: on the Curvature of Deep Generative Models

Autori: G. Arvanitidis, L.K. Hansen and S. Hauberg
Pubblicato in: International Conference on Learning Representations (ICLR), 2018
Editore: International Conference on Learning Representations (ICLR)

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

Autori: Frederik Warburg, Søren Hauberg, Manuel López-Antequera, Pau Gargallo, Yubin Kuang, Javier Civera
Pubblicato in: Computer Vision and Pattern Recognition, 2020
Editore: IEEE

Explicit Disentanglement of Appearance and Perspective in Generative Models

Autori: Nicki Skafte Detlefsen, Søren Hauberg
Pubblicato in: NeurIPS, 2019
Editore: NeurIPS

Reliable training and estimation of variance networks

Autori: Detlefsen, Nicki S.; Jørgensen, Martin; Hauberg, Søren
Pubblicato in: Advances in Neural Information Processing Systems (NeurIPS), Numero 2, 2019
Editore: NeurIPS

Directional Statistics with the Spherical Normal Distribution

Autori: Søren Hauberg
Pubblicato in: International Conference on Information Fusion (FUSION), 2018
Editore: IEEE
DOI: 10.23919/icif.2018.8455242

Variational Autoencoders with Riemannian Brownian Motion Priors

Autori: Dimitris Kalatzis, David Eklund, Georgios Arvanitidis Søren Hauberg
Pubblicato in: International Conference on Machine Learning, 2020
Editore: PMLR

On the Geometry of Latent Variable Models

Autori: Søren Hauberg
Pubblicato in: 2018
Editore: Oberwolfach

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

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

Benchmarking Generative Latent Variable Models for Speech

Autori: Jakob Drachmann Havtorn, Lasse Borgholt, Søren Hauberg, Jes Frellsen, Lars Maaløe
Pubblicato in: ICLR Workshop on Deep Generative Models for Highly Structured Data, 2022
Editore: OpenReview

Revisiting Active Sets for Gaussian Process Decoders

Autori: Pablo Moreno-Muñoz, Cilie Feldager, Søren Hauberg
Pubblicato in: Advances in Neural Information Processing Systems, 2022
Editore: Curran Associates, Inc.

Spontaneous Symmetry Breaking in Data Visualization

Autori: Cilie W. Feldager, Søren Hauberg, Lars Kai Hansen
Pubblicato in: ICANN, 2021, ISBN 978-3-030-86339-5
Editore: Springer
DOI: 10.1007/978-3-030-86340-1_35

Isometric Gaussian Process Latent Variable Model for Dissimilarity Data

Autori: Jørgensen, Martin; Hauberg, Søren
Pubblicato in: International Conference on Machine Learning, 2021
Editore: Proceedings of Machine Learning Research

Laplacian Autoencoders for Learning Stochastic Representations

Autori: Marco Miani, Frederik Warburg, Pablo Moreno-Muñoz, Nicki Skafte, Søren Hauberg
Pubblicato in: Advances in Neural Information Processing Systems, 2022
Editore: Curran Associates, Inc.

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

Autori: Andrea Vallone, Frederik Warburg, Hans Hansen, Søren Hauberg, Javier Civera
Pubblicato in: IEEE Robotics and Automation Letters, 2022, ISSN 2377-3766
Editore: IEEE
DOI: 10.1109/lra.2022.3187491

Learning meaningful representations of protein sequences

Autori: Nicki Skafte Detlefsen, Søren Hauberg, Wouter Boomsma
Pubblicato in: Nature Communications, 2022, ISSN 2041-1723
Editore: Nature Publishing Group
DOI: 10.1038/s41467-022-29443-w

Intrinsic Grassmann Averages for Online Linear Robust and Nonlinear Subspace Learning

Autori: Rudrasis Chakraborty, Liu Yang, Søren Hauberg, Baba C. Vemuri.
Pubblicato in: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020, ISSN 1939-3539
Editore: IEEE

Parallel QR factorization of block-tridiagonal matrices

Autori: Alfredo Buttari, Søren Hauberg, Costy Kodsi
Pubblicato in: SIAM Journal on Scientific Computing, 2019, ISSN 1064-8275
Editore: Society for Industrial and Applied Mathematics
DOI: 10.1137/19m1306166

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

Autori: S.A. Zahedi; C. Kodsi; Filippo Berto
Pubblicato in: Theoretical and Applied Fracture Mechanics, 2019, ISSN 0167-8442
Editore: 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

Autori: Costy Kodsi, Andrey P. Jivkov
Pubblicato in: SIAM Journal on Applied Mathematics, 2021, ISSN 0036-1399
Editore: 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)

Autori: Hauberg, Søren
Pubblicato in: Numero 1, 2019
Editore: arxiv.org

Geodesic Clustering in Deep Generative Models

Autori: Yang, Tao; Arvanitidis, Georgios; Fu, Dongmei; Li, Xiaogang; Hauberg, Søren
Pubblicato in: Numero 2, 2018
Editore: arxiv

Expected path length on random manifolds

Autori: David Eklund, Søren Hauberg
Pubblicato in: 2019
Editore: arXiv

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