Martin Jørgensen

According to our database, Martin Jørgensen authored at least 15 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

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

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

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Bayesian Quadrature for Neural Ensemble Search.

Saad Hamid, Xingchen Wan, Martin Jørgensen, Binxin Ru, Michael A. Osborne

Trans. Mach. Learn. Res., 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

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

2022

Probabilistic spatial transformer networks.

Pola Schwöbel, Frederik Rahbæk Warburg, Martin Jørgensen, Kristoffer Hougaard Madsen, Søren Hauberg

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Bezier Gaussian Processes for Tall and Wide Data.

Martin Jørgensen, Michael A. Osborne

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination.

Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Last Layer Marginal Likelihood for Invariance Learning.

Pola Schwöbel, Martin Jørgensen, Sebastian W. Ober, Mark van der Wilk

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Isometric Gaussian Process Latent Variable Model for Dissimilarity Data.

Martin Jørgensen, Søren Hauberg

Proceedings of the 38th International Conference on Machine Learning, 2021

Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval.

Frederik Warburg, Martin Jørgensen, Javier Civera, Søren Hauberg

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Reparametrization Invariance in non-parametric Causal Discovery.

Martin Jørgensen, Søren Hauberg

CoRR, 2020

Probabilistic Spatial Transformers for Bayesian Data Augmentation.

Pola Schwöbel, Frederik Warburg, Martin Jørgensen, Kristoffer H. Madsen, Søren Hauberg

CoRR, 2020

Stochastic Differential Equations with Variational Wishart Diffusions.

Martin Jørgensen, Marc Peter Deisenroth, Hugh Salimbeni

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Reliable training and estimation of variance networks.

Nicki Skafte Detlefsen, Martin Jørgensen, Søren Hauberg

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019