Bayesian Diffusion Tensor Estimation with Spatial Priors. - Xuan Gu; Per Sidén; Bertil Wegmann; Anders Eklund 002; Mattias Villani; Hans Knutsson (CAIP (1), 2017)

Fast Bayesian whole-brain fMRI analysis with spatial 3D priors. - Per Sidén; Anders Eklund 002; David Bolin; Mattias Villani (NeuroImage, 2017)

Real-Time Robotic Search using Structural Spatial Point Processes. - Olov Andersson; Per Sidén; Johan Dahlin; Patrick Doherty 001; Mattias Villani (UAI, 2019)

Real-Time Robotic Search using Hierarchical Spatial Point Processes. - Olov Andersson; Per Sidén; Johan Dahlin; Patrick Doherty 001; Mattias Villani (CoRR, 2019)

Deep Gaussian Markov Random Fields. - Per Sidén; Fredrik Lindsten (ICML, 2020)

Anatomically Informed Bayesian Spatial Priors for FMRI Analysis. - David Abramian; Per Sidén; Hans Knutsson; Mattias Villani; Anders Eklund 002 (ISBI, 2020)

Scalable Bayesian spatial analysis with Gaussian Markov random fields ; Skalbar Bayesiansk spatial analys med Gaussiska Markov-fält. - Per Sidén (2020)

Scalable Deep Gaussian Markov Random Fields for General Graphs. - Joel Oskarsson; Per Sidén; Fredrik Lindsten (ICML, 2022)

Temporal Graph Neural Networks for Irregular Data. - Joel Oskarsson; Per Sidén; Fredrik Lindsten (AISTATS, 2023)

DINO as a von Mises-Fisher mixture model. - Hariprasath Govindarajan; Per Sidén; Jacob Roll; Fredrik Lindsten (ICLR, 2023)

On Partial Prototype Collapse in the DINO Family of Self-Supervised Methods. - Hariprasath Govindarajan; Per Sidén; Jacob Roll; Fredrik Lindsten (BMVC, 2024)