ML Anthology

Hauberg, Søren

47 publications

AISTATS 2025 Bayes Without Underfitting: Fully Correlated Deep Learning Posteriors via Alternating Projections Marco Miani, Hrittik Roy, Søren Hauberg
NeurIPS 2025 Connecting Neural Models Latent Geometries with Relative Geodesic Representations Hanlin Yu, Berfin Inal, Georgios Arvanitidis, Søren Hauberg, Francesco Locatello, Marco Fumero
ICML 2025 Geometric Contact Flows: Contactomorphisms for Dynamics and Control Andrea Testa, Søren Hauberg, Tamim Asfour, Leonel Rozo
ICML 2025 Identifying Metric Structures of Deep Latent Variable Models Stas Syrota, Yevgen Zainchkovskyy, Johnny Xi, Benjamin Bloem-Reddy, Søren Hauberg
ICLRW 2025 Identifying Metric Structures of Deep Latent Variable Models Stas Syrota, Yevgen Zainchkovskyy, Johnny Xi, Benjamin Bloem-Reddy, Søren Hauberg
AISTATS 2025 Riemann$^2$: Learning Riemannian Submanifolds from Riemannian Data Leonel Rozo, Miguel González-Duque, Noémie Jaquier, Søren Hauberg
NeurIPS 2025 VIKING: Deep Variational Inference with Stochastic Projections Samuel G. Fadel, Hrittik Roy, Nicholas Krämer, Yevgen Zainchkovskyy, Stas Syrota, Alejandro Valverde Mahou, Carl Henrik Ek, Søren Hauberg
NeurIPS 2024 A Survey and Benchmark of High-Dimensional Bayesian Optimization of Discrete Sequences Miguel González-Duque, Richard Michael, Simon Bartels, Yevgen Zainchkovskyy, Søren Hauberg, Wouter Boomsma
ICMLW 2024 Decoder Ensembling for Learned Latent Geometries Stas Syrota, Pablo Moreno-Muñoz, Søren Hauberg
NeurIPS 2024 Gradients of Functions of Large Matrices Nicholas Krämer, Pablo Moreno-Muñoz, Hrittik Roy, Søren Hauberg
ICML 2024 Improving Adversarial Energy-Based Model via Diffusion Process Cong Geng, Tian Han, Peng-Tao Jiang, Hao Zhang, Jinwei Chen, Søren Hauberg, Bo Li
ICLR 2024 Neural Contractive Dynamical Systems Hadi Beik Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo
NeurIPS 2024 Reparameterization Invariance in Approximate Bayesian Inference Hrittik Roy, Marco Miani, Carl Henrik Ek, Philipp Hennig, Marvin Pförtner, Lukas Tatzel, Søren Hauberg
NeurIPS 2024 Sketched Lanczos Uncertainty Score: A Low-Memory Summary of the Fisher Information Marco Miani, Lorenzo Beretta, Søren Hauberg
TMLR 2024 Variational Autoencoding of Dental Point Clouds Johan Ziruo Ye, Thomas Ørkild, Peter Lempel Søndergard, Søren Hauberg
NeurIPS 2023 Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval Frederik Warburg, Marco Miani, Silas Brack, Søren Hauberg
NeurIPSW 2023 Beyond Parameter Averaging in Model Aggregation Pol G. Recasens, Jordi Torres, Josep Lluis Berral, Søren Hauberg, Pablo Moreno-Muñoz
TMLR 2023 Identifying Latent Distances with Finslerian Geometry Alison Pouplin, David Eklund, Carl Henrik Ek, Søren Hauberg
NeurIPS 2023 Learning to Taste: A Multimodal Wine Dataset Thoranna Bender, Simon Sørensen, Alireza Kashani, Kristjan Eldjarn Hjorleifsson, Grethe Hyldig, Søren Hauberg, Serge Belongie, Frederik Warburg
NeurIPS 2023 On Masked Pre-Training and the Marginal Likelihood Pablo Moreno-Muñoz, Pol Garcia Recasens, Søren Hauberg
NeurIPS 2023 Riemannian Laplace Approximations for Bayesian Neural Networks Federico Bergamin, Pablo Moreno-Muñoz, Søren Hauberg, Georgios Arvanitidis
ICMLW 2023 Variational Point Encoding Deformation for Dental Modeling Johan Ziruo Ye, Thomas Ørkild, Peter Lempel Søndergard, Søren Hauberg
ICLRW 2022 Benchmarking Generative Latent Variable Models for Speech Jakob Drachmann Havtorn, Lasse Borgholt, Søren Hauberg, Jes Frellsen, Lars Maaløe
NeurIPSW 2022 Identifying Latent Distances with Finslerian Geometry Alison Pouplin, David Eklund, Carl Henrik Ek, Søren Hauberg
NeurIPS 2022 Laplacian Autoencoders for Learning Stochastic Representations Marco Miani, Frederik Warburg, Pablo Moreno-Muñoz, Nicki Skafte, Søren Hauberg
NeurIPSW 2022 Optimal Latent Transport Hrittik Roy, Søren Hauberg
UAI 2022 Probabilistic Spatial Transformer Networks Pola Schwöbel, Frederik Rahbæk Warburg, Martin Jørgensen, Kristoffer Hougaard Madsen, Søren Hauberg
NeurIPSW 2022 Probabilistic Thermal Stability Prediction Through Sparsity Promoting Transformer Representation Yevgen Zainchkovskyy, Jesper Ferkinghoff-Borg, Anja Bennett, Thomas Egebjerg, Nikolai Lorenzen, Per Jr. Greisen, Søren Hauberg, Carsten Stahlhut
NeurIPS 2022 Revisiting Active Sets for Gaussian Process Decoders Pablo Moreno-Muñoz, Cilie Feldager, Søren Hauberg
ICCV 2021 Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval Frederik Warburg, Martin Jørgensen, Javier Civera, Søren Hauberg
NeurIPS 2021 Bounds All Around: Training Energy-Based Models with Bidirectional Bounds Cong Geng, Jia Wang, Zhiyong Gao, Jes Frellsen, Søren Hauberg
ICML 2021 Hierarchical VAEs Know What They Don’t Know Jakob D. Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe
NeurIPS 2019 Explicit Disentanglement of Appearance and Perspective in Generative Models Nicki Skafte, Søren Hauberg
AISTATS 2019 Probabilistic Riemannian Submanifold Learning with Wrapped Gaussian Process Latent Variable Models Anton Mallasto, Søren Hauberg, Aasa Feragen
NeurIPS 2019 Reliable Training and Estimation of Variance Networks Nicki Skafte, Martin Jørgensen, Søren Hauberg
ICLR 2018 Latent Space Oddity: On the Curvature of Deep Generative Models Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg
NeurIPS 2016 A Locally Adaptive Normal Distribution Georgios Arvanitidis, Lars K. Hansen, Søren Hauberg
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
COLT 2016 Open Problem: Kernel Methods on Manifolds and Metric Spaces. What Is the Probability of a Positive Definite Geodesic Exponential Kernel? Aasa Feragen, Søren Hauberg
UAI 2014 Metrics for Probabilistic Geometries Alessandra Tosi, Søren Hauberg, Alfredo Vellido, Neil D. Lawrence
AISTATS 2014 Probabilistic Solutions to Differential Equations and Their Application to Riemannian Statistics Philipp Hennig, Søren Hauberg
NeurIPS 2012 A Geometric Take on Metric Learning Søren Hauberg, Oren Freifeld, Michael J. Black
ICCV 2011 Means in Spaces of Tree-like Shapes Aasa Feragen, Søren Hauberg, Mads Nielsen, François Lauze
ECCV 2010 GPU Accelerated Likelihoods for Stereo-Based Articulated Tracking Rune Møllegaard Friborg, Søren Hauberg, Kenny Erleben
ECCVW 2010 GPU Accelerated Likelihoods for Stereo-Based Articulated Tracking Rune Møllegaard Friborg, Søren Hauberg, Kenny Erleben
ECCV 2010 Gaussian-like Spatial Priors for Articulated Tracking Søren Hauberg, Stefan Sommer, Kim Steenstrup Pedersen
ECCV 2010 Manifold Valued Statistics, Exact Principal Geodesic Analysis and the Effect of Linear Approximations Stefan Sommer, François Lauze, Søren Hauberg, Mads Nielsen