Michael Riis Andersen

J. Mach. Learn. Res., 2024

Variance reduction of diffusion model's gradients with Taylor approximation-based control variate.

[BibT_eX]

[DOI]

Paul Jeha

Will Grathwohl

Carl Henrik Ek

CoRR, 2024

GAST: Geometry-Aware Structure Transformer.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2024

EB-NeRD a large-scale dataset for news recommendation.

[BibT_eX]

[DOI]

Proceedings of the Recommender Systems Challenge 2024, 2024

RecSys Challenge 2024: Balancing Accuracy and Editorial Values in News Recommendations.

[BibT_eX]

[DOI]

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

Neural machine translation for automated feedback on children's early-stage writing.

[BibT_eX]

[DOI]

Jonas Vestergaard Jensen

Mikkel Jordahn

Proceedings of the Northern Lights Deep Learning Conference, 2024

2023

Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming.

[BibT_eX]

[DOI]

Gabriel Riutort-Mayol

Paul-Christian Bürkner

Stat. Comput., 2023

Polygonizer: An auto-regressive building delineator.

[BibT_eX]

[DOI]

CoRR, 2023

On the role of Model Uncertainties in Bayesian Optimization.

[BibT_eX]

[DOI]

Jonathan Foldager

Mikkel Jordahn

CoRR, 2023

Automatic proficiency scoring for early-stage writing.

[BibT_eX]

[DOI]

Comput. Educ. Artif. Intell., 2023

On the role of model uncertainties in Bayesian optimisation.

[BibT_eX]

[DOI]

Jonathan Foldager

Mikkel Jordahn

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Creating the next generation of news experience on ekstrabladet.dk with recommender systems.

[BibT_eX]

[DOI]

Johannes Kruse

Kasper Lindskow

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Learning To Generate 3d Representations of Building Roofs Using Single-View Aerial Imagery.

[BibT_eX]

[DOI]

Alejandro Valverde Mahou

Alba Reinders Sánchez

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

SolarDK: A high-resolution urban solar panel image classification and localization dataset.

[BibT_eX]

[DOI]

Julius Holbech Radzikowski

Carl Anton Schmidt

Mathias Bonde Sørensen

Mads Andersen

CoRR, 2022

Robust, Automated, and Accurate Black-box Variational Inference.

[BibT_eX]

[DOI]

Manushi Welandawe

CoRR, 2022

2021

Uncertainty-aware sensitivity analysis using Rényi divergences.

[BibT_eX]

[DOI]

Topi Paananen

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Challenges and Opportunities in High Dimensional Variational Inference.

[BibT_eX]

[DOI]

Alejandro Catalina

Manushi Welandawe

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Preferential Batch Bayesian Optimization.

[BibT_eX]

[DOI]

Eero Siivola

Javier González

Pablo Garcia Moreno

Proceedings of the 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), 2021

2020

Robust, Accurate Stochastic Optimization for Variational Inference.

[BibT_eX]

[DOI]

Alejandro Catalina

Måns Magnusson

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Scalable Gaussian Process for Extreme Classification.

[BibT_eX]

[DOI]

Pablo Garcia Moreno

Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes.

[BibT_eX]

[DOI]

William J. Wilkinson

Paul E. Chang

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

Leave-One-Out Cross-Validation for Bayesian Model Comparison in Large Data.

[BibT_eX]

[DOI]

Måns Magnusson

Johan Jonasson

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

End-to-End Probabilistic Inference for Nonstationary Audio Analysis.

[BibT_eX]

[DOI]

William J. Wilkinson

Joshua D. Reiss

Dan Stowell

Proceedings of the 36th International Conference on Machine Learning, 2019

Bayesian leave-one-out cross-validation for large data.

[BibT_eX]

[DOI]

Måns Magnusson

Johan Jonasson

Proceedings of the 36th International Conference on Machine Learning, 2019

Unifying Probabilistic Models for Time-frequency Analysis.

[BibT_eX]

[DOI]

William J. Wilkinson

Joshua D. Reiss

Dan Stowell

Proceedings of the IEEE International Conference on Acoustics, 2019

Variable selection for Gaussian processes via sensitivity analysis of the posterior predictive distribution.

[BibT_eX]

[DOI]

Topi Paananen

Juho Piironen

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Correcting boundary over-Exploration Deficiencies in Bayesian Optimization with Virtual derivative Sign observations.

[BibT_eX]

[DOI]

Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018

Bayesian Structure Learning for Dynamic Brain Connectivity.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Probabilistic models for structured sparsity.

[BibT_eX]

[DOI]

PhD thesis, 2017

Bayesian Inference for Spatio-temporal Spike-and-Slab Priors.

[BibT_eX]

[DOI]

Ole Winther

J. Mach. Learn. Res., 2017

EEG source imaging assists decoding in a face recognition task.

[BibT_eX]

[DOI]

Rasmus S. Andersen

Anders U. Eliasen

Nicolai Pedersen

Sofie Therese Hansen

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2014

Bayesian Inference for Structured Spike and Slab Priors.

[BibT_eX]

[DOI]

Ole Winther

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

Learning the solution sparsity of an ill-posed linear inverse problem with the Variational Garrote.

[BibT_eX]

[DOI]

Sofie Therese Hansen