Reliable training and estimation of variance networks. - Nicki Skafte Detlefsen; Martin Jørgensen; Søren Hauberg (NeurIPS, 2019)

Stochastic Differential Equations with Variational Wishart Diffusions. - Martin Jørgensen; Marc Peter Deisenroth; Hugh Salimbeni (ICML, 2020)

Probabilistic Spatial Transformers for Bayesian Data Augmentation. - Pola Schwöbel; Frederik Warburg; Martin Jørgensen; Kristoffer H. Madsen; Søren Hauberg (CoRR, 2020)

Reparametrization Invariance in non-parametric Causal Discovery. - Martin Jørgensen; Søren Hauberg (CoRR, 2020)

Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval. - Frederik Warburg; Martin Jørgensen; Javier Civera 001; Søren Hauberg (ICCV, 2021)

Isometric Gaussian Process Latent Variable Model for Dissimilarity Data. - Martin Jørgensen; Søren Hauberg (ICML, 2021)

Last Layer Marginal Likelihood for Invariance Learning. - Pola Schwöbel; Martin Jørgensen; Sebastian W. Ober; Mark van der Wilk (AISTATS, 2022)

Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination. - Masaki Adachi; Satoshi Hayakawa; Martin Jørgensen; Harald Oberhauser; Michael A. Osborne (NeurIPS, 2022)

Bezier Gaussian Processes for Tall and Wide Data. - Martin Jørgensen; Michael A. Osborne (NeurIPS, 2022)

Probabilistic spatial transformer networks. - Pola Schwöbel; Frederik Rahbæk Warburg; Martin Jørgensen; Kristoffer Hougaard Madsen; Søren Hauberg (UAI, 2022)

SOBER: Scalable Batch Bayesian Optimization and Quadrature using Recombination Constraints. - Masaki Adachi; Satoshi Hayakawa; Saad Hamid; Martin Jørgensen; Harald Oberhauser; Michael A. Osborne (CoRR, 2023)

Domain-Agnostic Batch Bayesian Optimization with Diverse Constraints via Bayesian Quadrature. - Masaki Adachi; Satoshi Hayakawa; Xingchen Wan; Martin Jørgensen; Harald Oberhauser; Michael A. Osborne (CoRR, 2023)

Bayesian Quadrature for Neural Ensemble Search. - Saad Hamid; Xingchen Wan; Martin Jørgensen; Binxin Ru; Michael A. Osborne (Trans. Mach. Learn. Res., 2023)

Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach. - Masaki Adachi; Satoshi Hayakawa; Martin Jørgensen; Xingchen Wan; Vu Nguyen; Harald Oberhauser; Michael A. Osborne (AISTATS, 2024)

A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Lifting. - Masaki Adachi; Satoshi Hayakawa; Martin Jørgensen; Saad Hamid; Harald Oberhauser; Michael A. Osborne (CoRR, 2024)