activity
20172020
most citedAn Expectation-Maximization Algorithm for the Fractal Inverse Problem

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.AI2020

End-to-End Entity Classification on Multimodal Knowledge Graphs

W. X. Wilcke, P. Bloem, V. de Boer +2

End-to-end multimodal learning on knowledge graphs has been left largely unaddressed. Instead, most end-to-end models such as message passing networks learn solely from the relatio…

cs.CV2020

A Hybrid 3DCNN and 3DC-LSTM based model for 4D Spatio-temporal fMRI data: An ABIDE Autism Classification study

Ahmed El-Gazzar, Mirjam Quaak, Leonardo Cerliani +3

Functional Magnetic Resonance Imaging (fMRI) captures the temporal dynamics of neural activity as a function of spatial location in the brain. Thus, fMRI scans are represented as 4…

cs.CV2019

Exploiting Temporality for Semi-Supervised Video Segmentation

Radu Sibechi, Olaf Booij, Nora Baka +1

In recent years, there has been remarkable progress in supervised image segmentation. Video segmentation is less explored, despite the temporal dimension being highly informative.…

stat.ML2018

Three Tools for Practical Differential Privacy

Koen Lennart van der Veen, Ruben Seggers, Peter Bloem +1

Differentially private learning on real-world data poses challenges for standard machine learning practice: privacy guarantees are difficult to interpret, hyperparameter tuning on…

stat.ML20171 cited

An Expectation-Maximization Algorithm for the Fractal Inverse Problem

Peter Bloem, Steven de Rooij

We present an Expectation-Maximization algorithm for the fractal inverse problem: the problem of fitting a fractal model to data. In our setting the fractals are Iterated Function…