Marcel van Gerven

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 52

Top Topics

Variational Inference

Top Venues

Frontiers Comput. Neurosci.

Publications

Yuzhen Qin, Ahmed ElGazzar, Danielle S. Bassett, Fabio Pasqualetti, Marcel van Gerven
Analytical Characterization of Epileptic Dynamics in a Bistable System. CoRR (2024)
Sigur de Vries, Sander W. Keemink, Marcel van Gerven
Discovering Dynamic Symbolic Policies with Genetic Programming. CoRR (2024)
Ahmed ElGazzar, Marcel van Gerven
Universal Differential Equations as a Common Modeling Language for Neuroscience. CoRR (2024)
Jesús García Fernández, Sander W. Keemink, Marcel van Gerven
Gradient-Free Training of Recurrent Neural Networks using Random Perturbations. CoRR (2024)
Sander Dalm, Joshua Offergeld, Nasir Ahmad, Marcel van Gerven
Efficient Deep Learning with Decorrelated Backpropagation. CoRR (2024)
Joshua Offergeld, Marcel van Gerven, Nasir Ahmad
Subspace Node Pruning. CoRR (2024)
Hasan Mohamed, Bogdan Raducanu, Ilya Kiselev, Zuowen Wang, Burcu Küçükoglu, Bodo Rueckauer, Marcel van Gerven, Carolina Mora Lopez, Shih-Chii Liu
A 128-channel real-time VPDNN stimulation system for a visual cortical neuroprosthesis. BioCAS (2023)
Mahyar Shahsavari, David B. Thomas, Marcel van Gerven, Andrew D. Brown, Wayne Luk
Advancements in spiking neural network communication and synchronization techniques for event-driven neuromorphic systems. Array 20 (2023)
Nasir Ahmad, Ellen Schrader, Marcel van Gerven
Constrained Parameter Inference as a Principle for Learning. Trans. Mach. Learn. Res. 2023 (2023)
Sander Dalm, Marcel van Gerven, Nasir Ahmad
Effective Learning with Node Perturbation in Deep Neural Networks. CoRR (2023)
Sander Dalm, Nasir Ahmad, Luca Ambrogioni, Marcel van Gerven
Gradient-adjusted Incremental Target Propagation Provides Effective Credit Assignment in Deep Neural Networks. Trans. Mach. Learn. Res. 2023 (2023)
Nasir Ahmad, Ellen Schrader, Marcel van Gerven
Constrained Parameter Inference as a Principle for Learning. CoRR (2022)
Burcu Küçükoglu, Bodo Rueckauer, Nasir Ahmad, Jaap de Ruyter van Steveninck, Umut Güçlü, Marcel van Gerven
Optimization of Neuroprosthetic Vision via End-to-End Deep Reinforcement Learning. Int. J. Neural Syst. 32 (11) (2022)
Bodo Rueckauer, Marcel van Gerven
Experiencing Prosthetic Vision with Event-Based Sensors. ICONS (2022)
Justus F. Hübotter, Serge Thill, Marcel van Gerven, Pablo Lanillos
Learning Policies for Continuous Control via Transition Models. IWAI (2022)
Burcu Küçükoglu, Walraaf Borkent, Bodo Rueckauer, Nasir Ahmad, Umut Güçlü, Marcel van Gerven
Efficient Deep Reinforcement Learning with Predictive Processing Proximal Policy Optimization. CoRR (2022)
Justus F. Hübotter, Serge Thill, Marcel van Gerven, Pablo Lanillos
Learning Policies for Continuous Control via Transition Models. CoRR (2022)
Gabrielle Ras, Ning Xie, Marcel van Gerven, Derek Doran
Explainable Deep Learning: A Field Guide for the Uninitiated. J. Artif. Intell. Res. 73 (2022)
Sander Dalm, Nasir Ahmad, Luca Ambrogioni, Marcel van Gerven
Scaling up learning with GAIT-prop. CoRR (2021)
Nasir Ahmad, Bodo Rueckauer, Marcel van Gerven
Brain-inspired Learning Drives Advances in Neuromorphic Computing. ERCIM News 2021 (125) (2021)
Luca Ambrogioni, Kate Lin, Emily Fertig, Sharad Vikram, Max Hinne, Dave Moore, Marcel van Gerven
Automatic structured variational inference. AISTATS (2021)
Luca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven
Automatic variational inference with cascading flows. ICML (2021)
Pablo Lanillos, Marcel van Gerven
Neuroscience-inspired perception-action in robotics: applying active inference for state estimation, control and self-perception. CoRR (2021)
Luca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven
Automatic variational inference with cascading flows. CoRR (2021)
Linda Geerligs, Marcel van Gerven, Umut Güçlü
Detecting neural state transitions underlying event segmentation. NeuroImage 236 (2021)
Thomas Rood, Marcel van Gerven, Pablo Lanillos
A Deep Active Inference Model of the Rubber-Hand Illusion. IWAI (2020)
Thomas Rood, Marcel van Gerven, Pablo Lanillos
A deep active inference model of the rubber-hand illusion. CoRR (2020)
Caner Mercan, G. C. A. M. Mooij, David Tellez, Johannes Lotz, Nick Weiss, Marcel van Gerven, Francesco Ciompi
Virtual Staining for Mitosis Detection in Breast Histopathology. ISBI (2020)
Caner Mercan, Germonda Reijnen-Mooij, David Tellez Martin, Johannes Lotz, Nick Weiss, Marcel van Gerven, Francesco Ciompi
Virtual staining for mitosis detection in Breast Histopathology. CoRR (2020)
Patrick Dallaire, Luca Ambrogioni, Ludovic Trottier, Umut Güçlü, Max Hinne, Philippe Giguère, Brahim Chaib-draa, Marcel van Gerven, François Laviolette
The Indian Chefs Process. CoRR (2020)
Ning Xie, Gabrielle Ras, Marcel van Gerven, Derek Doran
Explainable Deep Learning: A Field Guide for the Uninitiated. CoRR (2020)
Luca Ambrogioni, Max Hinne, Marcel van Gerven
Automatic structured variational inference. CoRR (2020)
Patrick Dallaire, Luca Ambrogioni, Ludovic Trottier, Umut Güçlü, Max Hinne, Philippe Giguère, Marcel van Gerven, François Laviolette
The Indian Chefs Process. UAI (2020)
Sushrut Thorat, Marcel van Gerven, Marius V. Peelen
The functional role of cue-driven feature-based feedback in object recognition. CoRR (2019)
Gabrielle Ras, Luca Ambrogioni, Umut Güçlü, Marcel van Gerven
Temporal Factorization of 3D Convolutional Kernels. BNAIC/BENELEARN (2019)
Luca Ambrogioni, Umut Güçlü, Julia Berezutskaya, Eva W. P. van den Borne, Yagmur Güçlütürk, Max Hinne, Eric Maris, Marcel van Gerven
Forward Amortized Inference for Likelihood-Free Variational Marginalization. AISTATS (2019)
Luca Ambrogioni, Patrick Ebel, Max Hinne, Umut Güçlü, Marcel van Gerven, Eric Maris
SpikeCaKe: Semi-Analytic Nonparametric Bayesian Inference for Spike-Spike Neuronal Connectivity. AISTATS (2019)
Luca Ambrogioni, Umut Güçlü, Marcel van Gerven
k-GANs: Ensemble of Generative Models with Semi-Discrete Optimal Transport. CoRR (2019)
Luca Ambrogioni, Umut Güçlü, Yagmur Güçlütürk, Marcel van Gerven
Wasserstein Variational Gradient Descent: From Semi-Discrete Optimal Transport to Ensemble Variational Inference. CoRR (2018)
Gabrielle Ras, Marcel van Gerven, Pim Haselager
Explanation Methods in Deep Learning: Users, Values, Concerns and Challenges. CoRR (2018)
Marjolein Troost, Katja Seeliger, Marcel van Gerven
Generalization of an Upper Bound on the Number of Nodes Needed to Achieve Linear Separability. CoRR (2018)
Katja Seeliger, M. Fritsche, Umut Güçlü, Sanne Schoenmakers, Jan-Mathijs Schoffelen, Sander E. Bosch, Marcel van Gerven
Convolutional neural network-based encoding and decoding of visual object recognition in space and time. NeuroImage 180 (Part) (2018)
Chris I. Baker, Marcel van Gerven
New advances in encoding and decoding of brain signals. NeuroImage 180 (Part) (2018)
Marcel van Gerven
Computational Foundations of Natural Intelligence. Frontiers Comput. Neurosci. 11 (2017)
Yagmur Güçlütürk, Umut Güçlü, Katja Seeliger, Sander E. Bosch, Rob van Lier, Marcel van Gerven
Deep adversarial neural decoding. CoRR (2017)
Marcel van Gerven, Sander M. Bohté
Editorial: Artificial Neural Networks as Models of Neural Information Processing. Frontiers Comput. Neurosci. 11 (2017)
Luca Ambrogioni, Max Hinne, Marcel van Gerven, Eric Maris
GP CaKe: Effective brain connectivity with causal kernels. NIPS (2017)
Edward Grant, Pushmeet Kohli, Marcel van Gerven
Deep Disentangled Representations for Volumetric Reconstruction. ECCV Workshops (3) (2016)
Umut Güçlü, Jordy Thielen, Michael Hanke, Marcel van Gerven, Marcel A. J. van Gerven
Brains on Beats. NIPS (2016)
Marieke E. van de Nieuwenhuijzen, Nikolai Axmacher, Jürgen Fell, Carina Renate Oehrn, Ole Jensen, Marcel van Gerven
Decoding of task-relevant and task-irrelevant intracranial EEG representations. NeuroImage 137 (2016)
Edward Grant, Stephan Sahm, Mariam Zabihi, Marcel van Gerven
Predicting and visualizing psychological attributions with a deep neural network. ICPR (2016)
Edward Grant, Pushmeet Kohli, Marcel van Gerven
Deep disentangled representations for volumetric reconstruction. CoRR (2016)
Edward Grant, Stephan Sahm, Mariam Zabihi, Marcel van Gerven
Predicting psychological attributions from face photographs with a deep neural network. CoRR (2015)
Sanne Schoenmakers, Tom Heskes, Marcel van Gerven
Hidden Markov Models for Reading Words from the Human Brain. PRNI (2015)
Sanne Schoenmakers, Marcel van Gerven, Tom Heskes
Gaussian mixture models improve fMRI-based image reconstruction. PRNI (2014)
Sanne Schoenmakers, Umut Güçlü, Marcel van Gerven, Tom Heskes
Gaussian mixture models and semantic gating improve reconstructions from human brain activity. Frontiers Comput. Neurosci. 8 (2014)
Sanne Schoenmakers, Markus Barth, Tom Heskes, Marcel van Gerven
Linear reconstruction of perceived images from human brain activity. NeuroImage 83 (2013)
Marcel van Gerven, Peter Kok, Floris P. de Lange, Tom Heskes
Dynamic decoding of ongoing perception. NeuroImage 57 (3) (2011)
Marcel van Gerven, Eric Maris, Tom Heskes
A Markov Random Field Approach to Neural Encoding and Decoding. ICANN (2) (2011)
Marcel van Gerven, Floris P. de Lange, Tom Heskes
Neural Decoding with Hierarchical Generative Models. Neural Comput. 22 (12) (2010)
Marcel van Gerven, Botond Cseke, Robert Oostenveld, Tom Heskes
Bayesian Source Localization with the Multivariate Laplace Prior. NIPS (2009)
Marcel van Gerven, Ali Bahramisharif, Tom Heskes, Ole Jensen
Selecting features for BCI control based on a covert spatial attention paradigm. Neural Networks 22 (9) (2009)
Don Willems, Ralph Niels, Marcel van Gerven, Louis Vuurpijl
Iconic and multi-stroke gesture recognition. Pattern Recognit. 42 (12) (2009)
Marcel van Gerven, Christian Hesse, Ole Jensen, Tom Heskes
Interpreting single trial data using groupwise regularisation. NeuroImage 46 (3) (2009)
Ali Bahramisharif, Marcel van Gerven, Tom Heskes
Exploring the impact of alternative feature representations on BCI classification. ESANN (2009)
Marcel van Gerven, Peter J. F. Lucas, Theo P. van der Weide
A generic qualitative characterization of independence of causal influence. Int. J. Approx. Reason. 48 (1) (2008)
Marcel van Gerven, Babs G. Taal, Peter J. F. Lucas
Dynamic Bayesian networks as prognostic models for clinical patient management. J. Biomed. Informatics 41 (4) (2008)
Marcel van Gerven, Francisco Javier Díez, Babs G. Taal, Peter J. F. Lucas
Selecting treatment strategies with dynamic limited-memory influence diagrams. Artif. Intell. Medicine 40 (3) (2007)
Marcel van Gerven, Rasa Jurgelenaite, Babs G. Taal, Tom Heskes, Peter J. F. Lucas
Predicting carcinoid heart disease with the noisy-threshold classifier. Artif. Intell. Medicine 40 (1) (2007)
Marcel van Gerven, Francisco Javier Díez
Selecting Strategies for Infinite-Horizon Dynamic LIMIDS. Probabilistic Graphical Models (2006)
Marcel van Gerven, Peter J. F. Lucas, Theo P. van der Weide
A Qualitative Characterisation of Causal Independence Models Using Boolean Polynomials. ECSQARU (2005)
Marcel van Gerven
Guidelines for Probabilistic Model Qualification. BNAIC (2005)
Marcel van Gerven, Peter J. F. Lucas
Using Background Knowledge to Construct Bayesian Classifiers for Data-Poor Domains. SGAI Conf. (2004)
Marcel van Gerven, Peter J. F. Lucas
Employing Maximum Mutual Information for Bayesian Classification. ISBMDA (2004)