output
20022026
most citedA Deep Learning Framework for Unsupervised Affine and Deformable Image Registration

843 citations

Showing 2016Show all

18 papers · 1 filter

stat.ML2016★ 1 cited

RSSL: Semi-supervised Learning in R

Jesse H. Krijthe

In this paper, we introduce a package for semi-supervised learning research in the R programming language called RSSL. We cover the purpose of the package, the methods it includes…

physics.med-ph2016

Flexible and compact hybrid metasurfaces for enhanced ultra high field in vivo magnetic resonance imaging

Rita Schmidt, Alexey Slobozhanyuk, Pavel Belov +1

Developments in metamaterials and related structures such as metasurfaces have opened up new possibilities in designing materials and devices with unique properties. The main progr…

stat.ML2016★ 4 cited

The Pessimistic Limits and Possibilities of Margin-based Losses in Semi-supervised Learning

Jesse H. Krijthe, Marco Loog

Consider a classification problem where we have both labeled and unlabeled data available. We show that for linear classifiers defined by convex margin-based surrogate losses that…

cs.CV2016★ 19 cited

A Novel Motion Detection Method Resistant to Severe Illumination Changes

Sahar Yousefi, M. T. Manzuri Shalmani, Jeremy Lin +1

Recently, there has been a considerable attention given to the motion detection problem due to the explosive growth of its applications in video analysis and surveillance systems.…

stat.AP2016★ 2 cited

Secondary Phenotype Analysis in Ascertained Family Designs: Application to the Leiden Longevity Study

Renaud Tissier, Roula Tsonaka, Simon P. Mooijaart +2

The case-control design is often used to test associations between the case-control status and genetic variants. In addition to this primary phenotype a number of additional traits…

stat.ME2016★ 46 cited

Simultaneous Control of All False Discovery Proportions in Large-Scale Multiple Hypothesis Testing

Jelle Goeman, Rosa Meijer, Thijmen Krebs +1

Closed testing procedures are classically used for familywise error rate (FWER) control, but they can also be used to obtain simultaneous confidence bounds for the false discovery…

stat.ML2016

The Peaking Phenomenon in Semi-supervised Learning

Jesse H. Krijthe, Marco Loog

For the supervised least squares classifier, when the number of training objects is smaller than the dimensionality of the data, adding more data to the training set may first incr…

physics.bio-ph2016★ 4 cited

Scroll-wave dynamics in the presence of ionic and conduction inhomogeneities in an anatomically realistic mathematical model for the pig heart

R. Majumder, R Pandit, A. V. Panfilov

Nonlinear waves of the reaction-diffusion (RD) type occur in many biophysical systems, including the heart, where they initiate cardiac contraction. Such waves can form vortices ca…

stat.ME2016★ 16 cited

Better-Than-Chance Classification for Signal Detection

Jonathan D. Rosenblatt, Yuval Benjamini, Roee Gilron +2

The estimated accuracy of a classifier is a random quantity with variability. A common practice in supervised machine learning, is thus to test if the estimated accuracy is signifi…

stat.ME2016

Common and Distinct Components in Data Fusion

Age K. Smilde, Ingrid Mage, Tormod Naes +5

In many areas of science multiple sets of data are collected pertaining to the same system. Examples are food products which are characterized by different sets of variables, bio-p…

stat.AP2016★ 5 cited

A penalized inference approach to stochastic block modelling of community structure in the Italian Parliament

Mirko Signorelli, Ernst C. Wit

We analyse bill cosponsorship networks in the Italian Chamber of Deputies. In comparison with other parliaments, a distinguishing feature of the Chamber is the large number of poli…

stat.ME2016

Transformation, normalization and batch effect in the analysis of mass spectrometry data for omics studies

Bart J. A. Mertens

Data transformation, normalization and handling of batch effect are a key part of data analysis for almost all spectrometry-based omics data. This paper reviews and contrasts these…

stat.ME2016★ 2 cited

Semiparametric two-component mixture models under L-moments constraints

Diaa Al Mohamad

We propose a structure of a semiparametric two-component mixture model when one component is parametric and the other is defined through L-moments conditions. Estimation of a two-c…

physics.med-ph2016★ 589 cited

Major depression as a complex dynamic system

Angélique O. J. Cramer, Claudia D. van Borkulo, Erik J. Giltay +4

In this paper, we characterize major depression (MD) as a complex dynamical system in which symptoms (e.g., insomnia and fatigue) are directly connected to one another in a network…

q-bio.PE2016★ 1 cited

Inferring in emerging epidemics - the effect of common population structure is small

Pieter Trapman, Frank Ball, Jean-Stéphane Dhersin +3

When controlling an emerging outbreak of an infectious disease it is essential to know the key epidemiological parameters, such as the basic reproduction number and the contr…

q-bio.QM2016★ 25 cited

PyPanda: a Python Package for Gene Regulatory Network Reconstruction

David G. P. van IJzendoorn, Kimberly Glass, John Quackenbush +1

PANDA (Passing Attributes between Networks for Data Assimilation) is a gene regulatory network inference method that uses message-passing to integrate multiple sources of 'omics da…

stat.ME2016★ 2 cited

Semiparametric two-component mixture models under linear constraints

Diaa Al Mohamad, Assia Boumahdaf

We propose a structure of a semiparametric two-component mixture model when one component is parametric and the other is defined through linear constraints on its distribution func…

stat.ME2016★ 2 cited

Statistical development and assessment of summary measures to account for isotopic clustering of Fourier transform mass spectrometry data in clinical diagnostic studies

Alexia Kakourou, Werner Vach, Simone Nicolardi +2

Mass spectrometry based clinical proteomics has emerged as a powerful tool for highthroughput protein profiling and biomarker discovery. Recent improvements in mass spectrometry te…