Martin Jørgensen

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 23

Top Topics

Stochastic Differential Equations

Retrieval Precision

Bayesian Inference

Dempster Shafer

Top Venues

Publications

Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Xingchen Wan, Vu Nguyen, Harald Oberhauser, Michael A. Osborne
Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach. AISTATS (2024)
Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Saad Hamid, Harald Oberhauser, Michael A. Osborne
A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Lifting. CoRR (2024)
Masaki Adachi, Satoshi Hayakawa, Saad Hamid, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne
SOBER: Scalable Batch Bayesian Optimization and Quadrature using Recombination Constraints. CoRR (2023)
Masaki Adachi, Satoshi Hayakawa, Xingchen Wan, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne
Domain-Agnostic Batch Bayesian Optimization with Diverse Constraints via Bayesian Quadrature. CoRR (2023)
Saad Hamid, Xingchen Wan, Martin Jørgensen, Binxin Ru, Michael A. Osborne
Bayesian Quadrature for Neural Ensemble Search. Trans. Mach. Learn. Res. 2023 (2023)
Saad Hamid, Xingchen Wan, Martin Jørgensen, Binxin Ru, Michael A. Osborne
Bayesian Quadrature for Neural Ensemble Search. CoRR (2023)
Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination. CoRR (2022)
Pola Schwöbel, Martin Jørgensen, Sebastian W. Ober, Mark van der Wilk
Last Layer Marginal Likelihood for Invariance Learning. AISTATS (2022)
Martin Jørgensen, Michael A. Osborne
Bezier Gaussian Processes for Tall and Wide Data. NeurIPS (2022)
Pola Schwöbel, Frederik Rahbæk Warburg, Martin Jørgensen, Kristoffer Hougaard Madsen, Søren Hauberg
Probabilistic spatial transformer networks. UAI (2022)
Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination. NeurIPS (2022)
Martin Jørgensen, Michael A. Osborne
Bézier Gaussian Processes for Tall and Wide Data. CoRR (2022)
Martin Jørgensen, Søren Hauberg
Isometric Gaussian Process Latent Variable Model for Dissimilarity Data. ICML (2021)
Pola Elisabeth Schwöbel, Martin Jørgensen, Sebastian W. Ober, Mark van der Wilk
Last Layer Marginal Likelihood for Invariance Learning. CoRR (2021)
Frederik Warburg, Martin Jørgensen, Javier Civera, Søren Hauberg
Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval. ICCV (2021)
Martin Jørgensen, Marc Peter Deisenroth, Hugh Salimbeni
Stochastic Differential Equations with Variational Wishart Diffusions. ICML (2020)
Martin Jørgensen, Søren Hauberg
Isometric Gaussian Process Latent Variable Model for Dissimilarity Data. CoRR (2020)
Frederik Warburg, Martin Jørgensen, Javier Civera, Søren Hauberg
Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval. CoRR (2020)
Pola Schwöbel, Frederik Warburg, Martin Jørgensen, Kristoffer H. Madsen, Søren Hauberg
Probabilistic Spatial Transformers for Bayesian Data Augmentation. CoRR (2020)
Martin Jørgensen, Søren Hauberg
Reparametrization Invariance in non-parametric Causal Discovery. CoRR (2020)
Martin Jørgensen, Marc Peter Deisenroth, Hugh Salimbeni
Stochastic Differential Equations with Variational Wishart Diffusions. CoRR (2020)
Nicki Skafte Detlefsen, Martin Jørgensen, Søren Hauberg
Reliable training and estimation of variance networks. NeurIPS (2019)
Nicki Skafte Detlefsen, Martin Jørgensen, Søren Hauberg
Reliable training and estimation of variance networks. CoRR (2019)