1.1k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Radboud University NijmegenNL50 papers
- Radboud University Medical CenterNL11 papers
- Delft University of TechnologyNL5 papers
- Donders Centre for NeuroscienceNL4 papers
- Harvard UniversityUS3 papers
- Jülich Aachen Research AllianceDE3 papers
- King's College LondonGB3 papers
- Technical University of MunichDE3 papers
- Bernstein Center for Computational Neuroscience GöttingenDE2 papers
- Brigham and Women's HospitalUS2 papers
- Columbia UniversityUS2 papers
- Eindhoven University of TechnologyNL2 papers
55 papers
Phenomenological modeling of diverse and heterogeneous synaptic dynamics at natural density
Agnes Korcsak-Gorzo, Charl Linssen, Jasper Albers +9
This chapter sheds light on the synaptic organization of the brain from the perspective of computational neuroscience. It provides an introductory overview on how to account for em…
Pseudo-CTs from T1-weighted MRI for planning of low-intensity transcranial focused ultrasound neuromodulation: an open-source tool
Siti Nurbaya Yaakub, Tristan A. White, Eric Kerfoot +3
Background: Individual skull models of bone density and geometry are important when planning the expected transcranial ultrasound acoustic field and estimating mechanical and therm…
Click prediction boosting via Bayesian hyperparameter optimization based ensemble learning pipelines
Çağatay Demirel, A. Aylin Tokuç, Ahmet Tezcan Tekin
Online travel agencies (OTA's) advertise their website offers on meta-search bidding engines. The problem of predicting the number of clicks a hotel would receive for a given bid a…
The world seems different in a social context: a neural network analysis of human experimental data
Maria Tsfasman, Anja Philippsen, Carlo Mazzola +3
Human perception and behavior are affected by the situational context, in particular during social interactions. A recent study demonstrated that humans perceive visual stimuli dif…
Constrained Sampling from a Kernel Density Estimator to Generate Scenarios for the Assessment of Automated Vehicles
Erwin de Gelder, Eric Cator, Jan-Pieter Paardekooper +2
The safety assessment of automated vehicles (AVs) is an important aspect of the development cycle of AVs. A scenario-based assessment approach is accepted by many players in the fi…
Exact results on high-dimensional linear regression via statistical physics
Alexander Mozeika, Mansoor Sheikh, Fabian Aguirre-Lopez +2
It is clear that conventional statistical inference protocols need to be revised to deal correctly with the high-dimensional data that are now common. Most recent studies aimed at…
Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors
Gerda Bortsova, Cristina González-Gonzalo, Suzanne C. Wetstein +9
Adversarial attacks are considered a potentially serious security threat for machine learning systems. Medical image analysis (MedIA) systems have recently been argued to be vulner…
Real-World Scenario Mining for the Assessment of Automated Vehicles
Erwin de Gelder, Jeroen Manders, Corrado Grappiolo +3
Scenario-based methods for the assessment of Automated Vehicles (AVs) are widely supported by many players in the automotive field. Scenarios captured from real-world data can be u…
An atomic Boltzmann machine capable of on-chip learning
Brian Kiraly, Elze J. Knol, Hilbert J. Kappen +1
The Boltzmann Machine (BM) is a neural network composed of stochastically firing neurons that can learn complex probability distributions by adapting the synaptic interactions betw…
A censored mixture model for modeling risk taking
Nienke F. S. Dijkstra, Henning Tiemeier, Bernd C. Figner +1
Risk behavior can have substantial consequences for health, well-being, and functioning. Previous studies have shown an association between real-world risk behavior and risk behavi…
Towards an Ontology for Scenario Definition for the Assessment of Automated Vehicles: An Object-Oriented Framework
E. de Gelder, J. -P. Paardekooper, A. Khabbaz Saberi +5
The development of new assessment methods for the performance of automated vehicles is essential to enable the deployment of automated driving technologies, due to the complex oper…
End-to-End Pixel-Based Deep Active Inference for Body Perception and Action
Cansu Sancaktar, Marcel van Gerven, Pablo Lanillos
We present a pixel-based deep active inference algorithm (PixelAI) inspired by human body perception and action. Our algorithm combines the free-energy principle from neuroscience,…
Iterative Augmentation of Visual Evidence for Weakly-Supervised Lesion Localization in Deep Interpretability Frameworks: Application to Color Fundus Images
Cristina González-Gonzalo, Bart Liefers, Bram van Ginneken +1
Interpretability of deep learning (DL) systems is gaining attention in medical imaging to increase experts' trust in the obtained predictions and facilitate their integration in cl…
Tracking Naturalistic Linguistic Predictions with Deep Neural Language Models
Micha Heilbron, Benedikt Ehinger, Peter Hagoort +1
Prediction in language has traditionally been studied using simple designs in which neural responses to expected and unexpected words are compared in a categorical fashion. However…
A deep learning model for segmentation of geographic atrophy to study its long-term natural history
Bart Liefers, Johanna M. Colijn, Cristina González-Gonzalo +6
Purpose: To develop and validate a deep learning model for automatic segmentation of geographic atrophy (GA) in color fundus images (CFIs) and its application to study growth rate…
A Review on Neural Network Models of Schizophrenia and Autism Spectrum Disorder
Pablo Lanillos, Daniel Oliva, Anja Philippsen +3
This survey presents the most relevant neural network models of autism spectrum disorder and schizophrenia, from the first connectionist models to recent deep network architectures…
Active inference body perception and action for humanoid robots
Guillermo Oliver, Pablo Lanillos, Gordon Cheng
Providing artificial agents with the same computational models of biological systems is a way to understand how intelligent behaviours may emerge. We present an active inference bo…
Implementing perceptron models with qubits
Roeland Wiersema, H. J. Kappen
We propose a method for learning a quantum probabilistic model of a perceptron. By considering a cross entropy between two density matrices we can learn a model that takes noisy ou…
The nature of the animacy organization in human ventral temporal cortex
Sushrut Thorat, Daria Proklova, Marius V. Peelen
The principles underlying the animacy organization of the ventral temporal cortex (VTC) remain hotly debated, with recent evidence pointing to an animacy continuum rather than a di…
Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration
Cristina González-Gonzalo, Verónica Sánchez-Gutiérrez, Paula Hernández-Martínez +5
Purpose: To validate the performance of a commercially-available, CE-certified deep learning (DL) system, RetCAD v.1.3.0 (Thirona, Nijmegen, The Netherlands), for the joint automat…
Recurrence is required to capture the representational dynamics of the human visual system
Tim C Kietzmann, Courtney J Spoerer, Lynn Sörensen +3
The human visual system is an intricate network of brain regions that enables us to recognize the world around us. Despite its abundant lateral and feedback connections, object pro…
DUNEuro -- A software toolbox for forward modeling in bioelectromagnetism
Sophie Schrader, Andreas Westhoff, Maria Carla Piastra +6
Accurate and efficient source analysis in electro- and magnetoencephalography using sophisticated realistic head geometries requires advanced numerical approaches. This paper prese…
Probabilistic Parameterized Polynomial Time
Nils Donselaar
We examine a parameterized complexity class for randomized computation where only the error bound and not the full runtime is allowed to depend more than polynomially on the parame…
Discourse Embellishment Using a Deep Encoder-Decoder Network
Leonid Berov, Kai Standvoss
We suggest a new NLG task in the context of the discourse generation pipeline of computational storytelling systems. This task, textual embellishment, is defined by taking a text a…