The following two papers were presented at MLSP 2016:
The influence of hyper-parameters in the infinite relational model by Kristoffer J. Albers, Morten Mørup, and Mikkel N. Schmidt.
Bayesian latent feature modeling for modeling bipartite networks with overlapping groups by Philip H. Jørgensen, Morten Mørup, Mikkel N. Schmidt, and Tue Herlau.
Poster presented at NIPS 2016 on “Completely random measures for modelling block-structured sparse networks” by Tue Herlau*, Mikkel Schmidt, and Morten Mørup.
link to paper
link to short video presentation
Article on “Quantifying functional connectivity in multi-subject fMRI data using component models” by Kristoffer H. Madsen,
Nathan W. Churchill, and Morten Mørup published in Human Brain Mapping. link to article
Two papers presented at Pattern Recognition and NeuroImaging 2016 (http://prni2016.wix.com/prni2016):
Astrid Engberg, Kasper Andersen, Morten Mørup, Kristoffer Madsen, Independent Vector Analysis for Capturing Common Components in fMRI Group Analysis.
Jesper Hinrich, Søren F. V. Nielsen, Kristoffer Madsen, Morten Mørup, Variational Group-PCA for Intrinsic Dimensionality Determination in fMRI Data.
Mikkel N. Schmidt presented the paper “Numerical approximations for speeding up MCMC inference in the infinite relational model” at EUSIPCO 2015.
Rasmus Røge presented the poster “Unsupervised Segmentation of Task Activated Regions in fMRI” at the Machine Learning for Signal Processing 2015 in Boston.
Morten Mørup gave a talk at ICML workshop on Statistics, Machine Learning and Neuroscience (Stamlins 2015) on Non-parametric Bayesian Modeling of Functional and Structural Brain Connectivity.