Michael Riis Andersen

Technical University of Denmark — Denmark

Computer Science · Physical Sciences

12h-index411citations52works4.32yr avg
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Research Topics

Gaussian Processes and Bayesian Inference(28), Advanced Multi-Objective Optimization Algorithms(12), Statistical Methods and Inference(9), Control Systems and Identification(6), Sparse and Compressive Sensing Techniques(5)

Publications52 total

Normative Alignment of Recommender Systems via Internal Label Shift
2025Open Access
Normative Alignment of Recommender Systems via Internal Label Shift
CBS Research Portal (Copenhagen Business School)·2025
EB-NeRD a large-scale dataset for news recommendation
2024· 18 citedOpen Access
RecSys Challenge 2024: Balancing Accuracy and Editorial Values in News Recommendations
2024· 10 citedOpen Access
NMR-Onion - a transparent multi-model based 1D NMR deconvolution algorithm
Heliyon·2024· 2 citedOpen Access
Variance reduction of diffusion model's gradients with Taylor approximation-based control variate
arXiv (Cornell University)·2024Open Access
A Framework for Improving the Reliability of Black-box Variational Inference.
PubMed·2024Open Access
Neural machine translation for automated feedback on children's early-stage writing
arXiv (Cornell University)·2023Open Access
Creating the next generation of news experience on ekstrabladet.dk with recommender systems
2023· 3 cited
Learning to Generate 3D Representations of Building Roofs Using Single-View Aerial Imagery
arXiv (Cornell University)·2023Open Access
On the role of Model Uncertainties in Bayesian Optimization
arXiv (Cornell University)·2023· 3 citedOpen Access
Automatic proficiency scoring for early-stage writing
Computers and Education Artificial Intelligence·2023· 4 citedOpen Access
Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming
Statistics and Computing·2022· 46 citedOpen Access
SolarDK: A high-resolution urban solar panel image classification and localization dataset
arXiv (Cornell University)·2022· 3 citedOpen Access
A Framework for Improving the Reliability of Black-box Variational Inference
arXiv (Cornell University)·2022· 4 citedOpen Access
Preferential Batch Bayesian Optimization
2021· 9 citedOpen Access
Uncertainty-aware sensitivity analysis using Rényi divergences
Uncertainty in Artificial Intelligence·2021
Challenges and Opportunities in High-dimensional Variational Inference
2021· 4 citedOpen Access
When Did the Train Arrive? A Bayesian Approach to Enrich Timetable Information Using Smart Card Data
IEEE Open Journal of Intelligent Transportation Systems·2021· 4 citedOpen Access
Robust, accurate stochastic optimization for variational inference
2020· 3 cited
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Frequent Co-authors

Aki Vehtari(23), Lars Kai Hansen(9), Jes Frellsen(9), Arno Solin(7), Topi Paananen(6), Akash Kumar Dhaka(6), Ole Winther(5), Kasper Lindskow(5), William J. Wilkinson(5), Gabriel Riutort‐Mayol(4), Måns Magnusson(4), Johannes Kruse(4), Jonathan H. Huggins(4), Eero Siivola(4), Javier González(4), Juho Piironen(3), Johan Jonasson(3), Alejandro Catalina(3), Pablo García Moreno(3), Joshua D. Reiss(3)