Martin Jørgensen

24 papers A* 6A 3Journal 15

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Fast post-process Bayesian inference with Variational Sparse Bayesian Quadrature. Stat. Comput. Chengkun Li, Grégoire Clarté, Martin Jørgensen, Luigi Acerbi
2024	J	`jnl`	A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Lifting. CoRR Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Saad Hamid, Harald Oberhauser, Michael A. Osborne
2024	A	`conf`	Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach. AISTATS Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Xingchen Wan, Vu Nguyen, Harald Oberhauser, Michael A. Osborne
2023	J	`jnl`	Bayesian Quadrature for Neural Ensemble Search. CoRR Saad Hamid, Xingchen Wan, Martin Jørgensen, Binxin Ru, Michael A. Osborne
2023	J	`jnl`	Bayesian Quadrature for Neural Ensemble Search. Trans. Mach. Learn. Res. Saad Hamid, Xingchen Wan, Martin Jørgensen, Binxin Ru, Michael A. Osborne
2023	J	`jnl`	Domain-Agnostic Batch Bayesian Optimization with Diverse Constraints via Bayesian Quadrature. CoRR Masaki Adachi, Satoshi Hayakawa, Xingchen Wan, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne
2023	J	`jnl`	SOBER: Scalable Batch Bayesian Optimization and Quadrature using Recombination Constraints. CoRR Masaki Adachi, Satoshi Hayakawa, Saad Hamid, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne
2022	A*	`conf`	Bezier Gaussian Processes for Tall and Wide Data. NeurIPS Martin Jørgensen, Michael A. Osborne
2022	J	`jnl`	Bézier Gaussian Processes for Tall and Wide Data. CoRR Martin Jørgensen, Michael A. Osborne
2022	A*	`conf`	Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination. NeurIPS Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne
2022	J	`jnl`	Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination. CoRR Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne
2022	A	`conf`	Last Layer Marginal Likelihood for Invariance Learning. AISTATS Pola Schwöbel, Martin Jørgensen, Sebastian W. Ober, Mark van der Wilk
2022	A	`conf`	Probabilistic spatial transformer networks. UAI Pola Schwöbel, Frederik Rahbæk Warburg, Martin Jørgensen, Kristoffer Hougaard Madsen, Søren Hauberg
2021	A*	`conf`	Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval. ICCV Frederik Warburg, Martin Jørgensen, Javier Civera, Søren Hauberg
2021	A*	`conf`	Isometric Gaussian Process Latent Variable Model for Dissimilarity Data. ICML Martin Jørgensen, Søren Hauberg
2021	J	`jnl`	Last Layer Marginal Likelihood for Invariance Learning. CoRR Pola Elisabeth Schwöbel, Martin Jørgensen, Sebastian W. Ober, Mark van der Wilk
2020	J	`jnl`	Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval. CoRR Frederik Warburg, Martin Jørgensen, Javier Civera, Søren Hauberg
2020	J	`jnl`	Isometric Gaussian Process Latent Variable Model for Dissimilarity Data. CoRR Martin Jørgensen, Søren Hauberg
2020	J	`jnl`	Probabilistic Spatial Transformers for Bayesian Data Augmentation. CoRR Pola Schwöbel, Frederik Warburg, Martin Jørgensen, Kristoffer H. Madsen, Søren Hauberg
2020	J	`jnl`	Reparametrization Invariance in non-parametric Causal Discovery. CoRR Martin Jørgensen, Søren Hauberg
2020	A*	`conf`	Stochastic Differential Equations with Variational Wishart Diffusions. ICML Martin Jørgensen, Marc Peter Deisenroth, Hugh Salimbeni
2020	J	`jnl`	Stochastic Differential Equations with Variational Wishart Diffusions. CoRR Martin Jørgensen, Marc Peter Deisenroth, Hugh Salimbeni
2019	A*	`conf`	Reliable training and estimation of variance networks. NeurIPS Nicki Skafte Detlefsen, Martin Jørgensen, Søren Hauberg
2019	J	`jnl`	Reliable training and estimation of variance networks. CoRR Nicki Skafte Detlefsen, Martin Jørgensen, Søren Hauberg