Andersen, Michael Riis

10 publications

AISTATS 2025 On Local Posterior Structure in Deep Ensembles Mikkel Jordahn, Jonas Vestergaard Jensen, Mikkel N. Schmidt, Michael Riis Andersen

JMLR 2024 A Framework for Improving the Reliability of Black-Box Variational Inference Manushi Welandawe, Michael Riis Andersen, Aki Vehtari, Jonathan H. Huggins

UAI 2024 Towards Scalable Bayesian Transformers: Investigating Stochastic Subset Selection for NLP Peter Johannes Tejlgaard Kampen, Gustav Ragnar Stoettrup Als, Michael Riis Andersen

ICMLW 2024 Variance Reduction of Diffusion Model's Gradients with Taylor Approximation-Based Control Variate Paul Jeha, Will Sussman Grathwohl, Michael Riis Andersen, Carl Henrik Ek, Jes Frellsen

NeurIPSW 2022 Publicly Available Privacy-Preserving Benchmarks for Polygenic Prediction Menno Witteveen, Emil Pedersen, Joeri Meijsen, Michael Riis Andersen, Florian Privé, Doug Speed, Bjarni Vilhjálmsson

ICMLW 2021 Challenges for BBVI with Normalizing Flows Akash Kumar Dhaka, Alejandro Catalina, Manushi Welandawe, Michael Riis Andersen, Jonathan H. Huggins, Aki Vehtari

UAI 2021 Uncertainty-Aware Sensitivity Analysis Using Rényi Divergences Topi Paananen, Michael Riis Andersen, Aki Vehtari

AISTATS 2019 Variable Selection for Gaussian Processes via Sensitivity Analysis of the Posterior Predictive Distribution Topi Paananen, Juho Piironen, Michael Riis Andersen, Aki Vehtari

AISTATS 2018 Bayesian Structure Learning for Dynamic Brain Connectivity Michael Riis Andersen, Ole Winther, Lars Kai Hansen, Russell A. Poldrack, Oluwasanmi Koyejo

JMLR 2017 Bayesian Inference for Spatio-Temporal Spike-and-Slab Priors Michael Riis Andersen, Aki Vehtari, Ole Winther, Lars Kai Hansen