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Marcel A. J. van Gerven
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2020 – today
- 2024
[i44]Ahmed ElGazzar, Marcel van Gerven:
Universal Differential Equations as a Common Modeling Language for Neuroscience. CoRR abs/2403.14510 (2024)- [i43]Yuzhen Qin, Ahmed ElGazzar, Danielle S. Bassett, Fabio Pasqualetti, Marcel van Gerven:
Analytical Characterization of Epileptic Dynamics in a Bistable System. CoRR abs/2404.03409 (2024) - [i42]Sander Dalm, Joshua Offergeld, Nasir Ahmad, Marcel van Gerven:
Efficient Deep Learning with Decorrelated Backpropagation. CoRR abs/2405.02385 (2024) - [i41]Jesús García Fernández, Sander W. Keemink, Marcel van Gerven:
Gradient-Free Training of Recurrent Neural Networks using Random Perturbations. CoRR abs/2405.08967 (2024) - [i40]Joshua Offergeld, Marcel van Gerven, Nasir Ahmad:
Subspace Node Pruning. CoRR abs/2405.17506 (2024) - [i39]Sigur de Vries, Sander W. Keemink, Marcel van Gerven:
Discovering Dynamic Symbolic Policies with Genetic Programming. CoRR abs/2406.02765 (2024) - [i38]Marzieh Hassanshahi Varposhti, Mahyar Shahsavari, Marcel van Gerven:
Energy-Efficient Spiking Recurrent Neural Network for Gesture Recognition on Embedded GPUs. CoRR abs/2408.12978 (2024) - [i37]Siddharth Chaturvedi, Ahmed ElGazzar, Marcel van Gerven:
Foragax: An Agent-Based Modelling Framework Based on JAX. CoRR abs/2409.06345 (2024) - [i36]Jesús García Fernández, Nasir Ahmad, Marcel van Gerven:
Ornstein-Uhlenbeck Adaptation as a Mechanism for Learning in Brains and Machines. CoRR abs/2410.13563 (2024) - 2023
- [j52]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: 100323 (2023) - [j51]Nasir Ahmad, Ellen Schrader, Marcel van Gerven:
Constrained Parameter Inference as a Principle for Learning. Trans. Mach. Learn. Res. 2023 (2023) - [j50]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) - [c39]Hasan Mohamed, Bogdan C. 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: 1-5 - [i35]Sander Dalm, Marcel van Gerven, Nasir Ahmad:
Effective Learning with Node Perturbation in Deep Neural Networks. CoRR abs/2310.00965 (2023) - 2022
- [j49]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): 2250052:1-2250052:16 (2022) - [j48]Gabrielle Ras, Ning Xie, Marcel van Gerven, Derek Doran:
Explainable Deep Learning: A Field Guide for the Uninitiated. J. Artif. Intell. Res. 73: 329-396 (2022) - [j47]Abdullahi Ali, Nasir Ahmad, Elgar de Groot, Marcel A. J. van Gerven, Tim Christian Kietzmann:
Predictive coding is a consequence of energy efficiency in recurrent neural networks. Patterns 3(12): 100639 (2022) - [j46]Júlio C. S. Jacques Júnior, Yagmur Güçlütürk, Marc Pérez, Umut Güçlü, Carlos Andújar, Xavier Baró, Hugo Jair Escalante, Isabelle Guyon, Marcel A. J. van Gerven, Rob van Lier, Sergio Escalera:
First Impressions: A Survey on Vision-Based Apparent Personality Trait Analysis. IEEE Trans. Affect. Comput. 13(1): 75-95 (2022) - [j45]Hugo Jair Escalante, Heysem Kaya, Albert Ali Salah, Sergio Escalera, Yagmur Güçlütürk, Umut Güçlü, Xavier Baró, Isabelle Guyon, Júlio C. S. Jacques Júnior, Meysam Madadi, Stéphane Ayache, Evelyne Viegas, Furkan Gürpinar, Achmadnoer Sukma Wicaksana, Cynthia C. S. Liem, Marcel A. J. van Gerven, Rob van Lier:
Modeling, Recognizing, and Explaining Apparent Personality From Videos. IEEE Trans. Affect. Comput. 13(2): 894-911 (2022) - [c38]Julia Berezutskaya, Luca Ambrogioni, Nick F. Ramsey, Marcel A. J. van Gerven:
Towards Naturalistic Speech Decoding from Intracranial Brain Data. EMBC 2022: 3100-3104 - [c37]Bodo Rueckauer, Marcel van Gerven:
Experiencing Prosthetic Vision with Event-Based Sensors. ICONS 2022: 20:1-20:7 - [c36]Justus F. Hübotter, Serge Thill, Marcel van Gerven, Pablo Lanillos:
Learning Policies for Continuous Control via Transition Models. IWAI 2022: 162-178 - [i34]Nasir Ahmad, Ellen Schrader, Marcel van Gerven:
Constrained Parameter Inference as a Principle for Learning. CoRR abs/2203.13203 (2022) - [i33]Justus F. Hübotter, Serge Thill, Marcel van Gerven, Pablo Lanillos:
Learning Policies for Continuous Control via Transition Models. CoRR abs/2209.08033 (2022) - [i32]Burcu Küçükoglu, Walraaf Borkent, Bodo Rueckauer, Nasir Ahmad, Umut Güçlü, Marcel van Gerven:
Efficient Deep Reinforcement Learning with Predictive Processing Proximal Policy Optimization. CoRR abs/2211.06236 (2022) - 2021
- [j44]Linda Geerligs, Marcel van Gerven, Umut Güçlü:
Detecting neural state transitions underlying event segmentation. NeuroImage 236: 118085 (2021) - [j43]Katja Seeliger, Luca Ambrogioni, Yagmur Güçlütürk, L. M. van den Bulk, Umut Güçlü, Marcel A. J. van Gerven:
End-to-end neural system identification with neural information flow. PLoS Comput. Biol. 17(2) (2021) - [c35]Luca Ambrogioni, Kate Lin, Emily Fertig, Sharad Vikram, Max Hinne, Dave Moore, Marcel van Gerven:
Automatic structured variational inference. AISTATS 2021: 676-684 - [c34]Luca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven:
Automatic variational inference with cascading flows. ICML 2021: 254-263 - [i31]Luca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven:
Automatic variational inference with cascading flows. CoRR abs/2102.04801 (2021) - [i30]Sander Dalm, Nasir Ahmad, Luca Ambrogioni, Marcel van Gerven:
Scaling up learning with GAIT-prop. CoRR abs/2102.11598 (2021) - [i29]Pablo Lanillos, Marcel van Gerven:
Neuroscience-inspired perception-action in robotics: applying active inference for state estimation, control and self-perception. CoRR abs/2105.04261 (2021) - [i28]Nasir Ahmad, Bodo Rueckauer, Marcel van Gerven:
Brain-inspired Learning Drives Advances in Neuromorphic Computing. ERCIM News 2021(125) (2021) - 2020
- [j42]Karen Sandø Ambrosen, Simon F. Eskildsen, Max Hinne, Kristine Krug, Henrik Lundell, Mikkel N. Schmidt, Marcel A. J. van Gerven, Morten Mørup, Tim B. Dyrby:
Validation of structural brain connectivity networks: The impact of scanning parameters. NeuroImage 204 (2020) - [j41]Alexander Ivanenko, Paul V. Watkins, Marcel A. J. van Gerven, K. Hammerschmidt, Bernhard Englitz:
Classifying sex and strain from mouse ultrasonic vocalizations using deep learning. PLoS Comput. Biol. 16(6) (2020) - [j40]Julia Berezutskaya, Zachary Freudenburg, Umut Güçlü, Marcel A. J. van Gerven, Nick F. Ramsey:
Brain-optimized extraction of complex sound features that drive continuous auditory perception. PLoS Comput. Biol. 16(7) (2020) - [c33]Cansu Sancaktar, Marcel A. J. van Gerven, Pablo Lanillos:
End-to-End Pixel-Based Deep Active Inference for Body Perception and Action. ICDL-EPIROB 2020: 1-8 - [c32]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: 1770-1774 - [c31]Thomas Rood, Marcel van Gerven, Pablo Lanillos:
A Deep Active Inference Model of the Rubber-Hand Illusion. IWAI 2020: 84-91 - [c30]Nasir Ahmad, Marcel A. J. van Gerven, Luca Ambrogioni:
GAIT-prop: A biologically plausible learning rule derived from backpropagation of error. NeurIPS 2020 - [c29]Patrick Dallaire, Luca Ambrogioni, Ludovic Trottier, Umut Güçlü, Max Hinne, Philippe Giguère, Marcel van Gerven, François Laviolette:
The Indian Chefs Process. UAI 2020: 600-608 - [i27]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 abs/2001.10657 (2020) - [i26]Luca Ambrogioni, Max Hinne, Marcel van Gerven:
Automatic structured variational inference. CoRR abs/2002.00643 (2020) - [i25]Nasir Ahmad, Luca Ambrogioni, Marcel A. J. van Gerven:
Spike-Timing-Dependent Inference of Synaptic Weights. CoRR abs/2003.03988 (2020) - [i24]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 abs/2003.07801 (2020) - [i23]Ning Xie, Gabrielle Ras, Marcel van Gerven, Derek Doran:
Explainable Deep Learning: A Field Guide for the Uninitiated. CoRR abs/2004.14545 (2020) - [i22]Nasir Ahmad, Marcel A. J. van Gerven, Luca Ambrogioni:
GAIT-prop: A biologically plausible learning rule derived from backpropagation of error. CoRR abs/2006.06438 (2020) - [i21]Gabriëlle Ras, Luca Ambrogioni, Pim Haselager, Marcel A. J. van Gerven, Umut Güçlü:
Explainable 3D Convolutional Neural Networks by Learning Temporal Transformations. CoRR abs/2006.15983 (2020) - [i20]Thomas Rood, Marcel van Gerven, Pablo Lanillos:
A deep active inference model of the rubber-hand illusion. CoRR abs/2008.07408 (2020)
2010 – 2019
- 2019
- [j39]Silvan C. Quax, Nadine Dijkstra, Mariel J. van Staveren, Sander E. Bosch, Marcel A. J. van Gerven:
Eye movements explain decodability during perception and cued attention in MEG. NeuroImage 195: 444-453 (2019) - [c28]Caroline J. M. Bollen, Umut Güçlü, Richard J. A. van Wezel, Marcel A. J. van Gerven, Yagmur Güçlütürk:
Simulating neuroprosthetic vision for emotion recognition. ACII Workshops 2019: 85-87 - [c27]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: 777-786 - [c26]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: 787-795 - [c25]Gabrielle Ras, Luca Ambrogioni, Umut Güçlü, Marcel van Gerven:
Temporal Factorization of 3D Convolutional Kernels. BNAIC/BENELEARN 2019 - [p2]Marcel A. J. van Gerven, Katja Seeliger, Umut Güçlü, Yagmur Güçlütürk:
Current Advances in Neural Decoding. Explainable AI 2019: 379-394 - [i19]Sushrut Thorat, Marcel van Gerven, Marius V. Peelen:
The functional role of cue-driven feature-based feedback in object recognition. CoRR abs/1903.10446 (2019) - [i18]Luca Ambrogioni, Umut Güçlü, Marcel van Gerven:
k-GANs: Ensemble of Generative Models with Semi-Discrete Optimal Transport. CoRR abs/1907.04050 (2019) - [i17]Sushrut Thorat, Giacomo Aldegheri, Marcel A. J. van Gerven, Marius V. Peelen:
Modulation of early visual processing alleviates capacity limits in solving multiple tasks. CoRR abs/1907.12309 (2019) - [i16]Max Hinne, Marcel A. J. van Gerven, Luca Ambrogioni:
Causal inference using Bayesian non-parametric quasi-experimental design. CoRR abs/1911.06722 (2019) - [i15]Gabriëlle Ras, Luca Ambrogioni, Umut Güçlü, Marcel A. J. van Gerven:
Temporal Factorization of 3D Convolutional Kernels. CoRR abs/1912.04075 (2019) - [i14]Gabriëlle Ras, Ron Dotsch, Luca Ambrogioni, Umut Güçlü, Marcel A. J. van Gerven:
Background Hardly Matters: Understanding Personality Attribution in Deep Residual Networks. CoRR abs/1912.09831 (2019) - 2018
- [j38]Chris I. Baker, Marcel van Gerven:
New advances in encoding and decoding of brain signals. NeuroImage 180(Part): 1-3 (2018) - [j37]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): 253-266 (2018) - [j36]Katja Seeliger, Umut Güçlü, Luca Ambrogioni, Yagmur Güçlütürk, Marcel A. J. van Gerven:
Generative adversarial networks for reconstructing natural images from brain activity. NeuroImage 181: 775-785 (2018) - [j35]Yagmur Güçlütürk, Umut Güçlü, Xavier Baró, Hugo Jair Escalante, Isabelle Guyon, Sergio Escalera, Marcel A. J. van Gerven, Rob van Lier:
Multimodal First Impression Analysis with Deep Residual Networks. IEEE Trans. Affect. Comput. 9(3): 316-329 (2018) - [c24]Luca Ambrogioni, Umut Güçlü, Yagmur Güçlütürk, Max Hinne, Marcel A. J. van Gerven, Eric Maris:
Wasserstein Variational Inference. NeurIPS 2018: 2478-2487 - [i13]Hugo Jair Escalante, Heysem Kaya, Albert Ali Salah, Sergio Escalera, Yagmur Güçlütürk, Umut Güçlü, Xavier Baró, Isabelle Guyon, Júlio C. S. Jacques Júnior, Meysam Madadi, Stéphane Ayache, Evelyne Viegas, Furkan Gürpinar, Achmadnoer Sukma Wicaksana, Cynthia C. S. Liem, Marcel A. J. van Gerven, Rob van Lier:
Explaining First Impressions: Modeling, Recognizing, and Explaining Apparent Personality from Videos. CoRR abs/1802.00745 (2018) - [i12]Marjolein Troost, Katja Seeliger, Marcel van Gerven:
Generalization of an Upper Bound on the Number of Nodes Needed to Achieve Linear Separability. CoRR abs/1802.03488 (2018) - [i11]Gabrielle Ras, Marcel van Gerven, Pim Haselager:
Explanation Methods in Deep Learning: Users, Values, Concerns and Challenges. CoRR abs/1803.07517 (2018) - [i10]Júlio C. S. Jacques Júnior, Yagmur Güçlütürk, Marc Pérez, Umut Güçlü, Carlos Andújar, Xavier Baró, Hugo Jair Escalante, Isabelle Guyon, Marcel A. J. van Gerven, Rob van Lier, Sergio Escalera:
First Impressions: A Survey on Computer Vision-Based Apparent Personality Trait Analysis. CoRR abs/1804.08046 (2018) - [i9]Luca Ambrogioni, Umut Güçlü, Yagmur Güçlütürk, Max Hinne, Marcel A. J. van Gerven, Eric Maris:
Wasserstein Variational Inference. CoRR abs/1805.11284 (2018) - [i8]Luca Ambrogioni, Umut Güçlü, Julia Berezutskaya, Eva W. P. van den Borne, Yagmur Güçlütürk, Max Hinne, Eric Maris, Marcel A. J. van Gerven:
Forward Amortized Inference for Likelihood-Free Variational Marginalization. CoRR abs/1805.11542 (2018) - [i7]Luca Ambrogioni, Umut Güçlü, Yagmur Güçlütürk, Marcel van Gerven:
Wasserstein Variational Gradient Descent: From Semi-Discrete Optimal Transport to Ensemble Variational Inference. CoRR abs/1811.02827 (2018) - 2017
- [j34]Umut Güçlü, Marcel A. J. van Gerven:
Modeling the Dynamics of Human Brain Activity with Recurrent Neural Networks. Frontiers Comput. Neurosci. 11: 7 (2017) - [j33]Marcel van Gerven:
Computational Foundations of Natural Intelligence. Frontiers Comput. Neurosci. 11: 112 (2017) - [j32]Marcel van Gerven, Sander M. Bohté:
Editorial: Artificial Neural Networks as Models of Neural Information Processing. Frontiers Comput. Neurosci. 11: 114 (2017) - [j31]Umut Güçlü, Marcel A. J. van Gerven:
Increasingly complex representations of natural movies across the dorsal stream are shared between subjects. NeuroImage 145: 329-336 (2017) - [j30]Max Hinne, Annet Meijers, Rembrandt Bakker, Paul H. E. Tiesinga, Morten Mørup, Marcel A. J. van Gerven:
The missing link: Predicting connectomes from noisy and partially observed tract tracing data. PLoS Comput. Biol. 13(1) (2017) - [j29]Luca Ambrogioni, Marcel A. J. van Gerven, Eric Maris:
Dynamic decomposition of spatiotemporal neural signals. PLoS Comput. Biol. 13(5) (2017) - [c23]Yagmur Güçlütürk, Umut Güçlü, Marc Pérez, Hugo Jair Escalante, Xavier Baró, Carlos Andújar, Isabelle Guyon, Júlio C. S. Jacques Júnior, Meysam Madadi, Sergio Escalera, Marcel A. J. van Gerven, Rob van Lier:
Visualizing Apparent Personality Analysis with Deep Residual Networks. ICCV Workshops 2017: 3101-3109 - [c22]Hugo Jair Escalante, Isabelle Guyon, Sergio Escalera, Júlio C. S. Jacques Júnior, Meysam Madadi, Xavier Baró, Stéphane Ayache, Evelyne Viegas, Yagmur Güçlütürk, Umut Güçlü, Marcel A. J. van Gerven, Rob van Lier:
Design of an explainable machine learning challenge for video interviews. IJCNN 2017: 3688-3695 - [c21]Luca Ambrogioni, Max Hinne, Marcel van Gerven, Eric Maris:
GP CaKe: Effective brain connectivity with causal kernels. NIPS 2017: 950-959 - [c20]Yagmur Güçlütürk, Umut Güçlü, Katja Seeliger, Sander E. Bosch, Rob van Lier, Marcel A. J. van Gerven:
Reconstructing perceived faces from brain activations with deep adversarial neural decoding. NIPS 2017: 4246-4257 - [i6]Umut Güçlü, Yagmur Güçlütürk, Meysam Madadi, Sergio Escalera, Xavier Baró, Jordi Gonzàlez, Rob van Lier, Marcel A. J. van Gerven:
End-to-end semantic face segmentation with conditional random fields as convolutional, recurrent and adversarial networks. CoRR abs/1703.03305 (2017) - [i5]Yagmur Güçlütürk, Umut Güçlü, Katja Seeliger, Sander E. Bosch, Rob van Lier, Marcel van Gerven:
Deep adversarial neural decoding. CoRR abs/1705.07109 (2017) - 2016
- [j28]Claudia S. Lüttke, Matthias Ekman, Marcel A. J. van Gerven, Floris P. de Lange:
Preference for Audiovisual Speech Congruency in Superior Temporal Cortex. J. Cogn. Neurosci. 28(1): 1-7 (2016) - [j27]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: 132-139 (2016) - [c19]Edward Grant, Pushmeet Kohli, Marcel van Gerven:
Deep Disentangled Representations for Volumetric Reconstruction. ECCV Workshops (3) 2016: 266-279 - [c18]Yagmur Güçlütürk, Umut Güçlü, Marcel A. J. van Gerven, Rob van Lier:
Deep Impression: Audiovisual Deep Residual Networks for Multimodal Apparent Personality Trait Recognition. ECCV Workshops (3) 2016: 349-358 - [c17]Yagmur Güçlütürk, Umut Güçlü, Rob van Lier, Marcel A. J. van Gerven:
Convolutional Sketch Inversion. ECCV Workshops (1) 2016: 810-824 - [c16]Edward Grant, Stephan Sahm, Mariam Zabihi, Marcel van Gerven:
Predicting and visualizing psychological attributions with a deep neural network. ICPR 2016: 1-6 - [c15]Umut Güçlü, Jordy Thielen, Michael Hanke, Marcel van Gerven, Marcel A. J. van Gerven:
Brains on Beats. NIPS 2016: 2101-2109 - [c14]Umut Güçlü, Jordy Thielen, Michael Hanke, Marcel van Gerven, Marcel A. J. van Gerven:
Brains on Beats. NIPS 2016: 2101-2109 - [i4]Yagmur Güçlütürk, Umut Güçlü, Rob van Lier, Marcel A. J. van Gerven:
Convolutional Sketch Inversion. CoRR abs/1606.03073 (2016) - [i3]Yagmur Güçlütürk, Umut Güçlü, Marcel A. J. van Gerven, Rob van Lier:
Deep Impression: Audiovisual Deep Residual Networks for Multimodal Apparent Personality Trait Recognition. CoRR abs/1609.05119 (2016) - [i2]Edward Grant, Pushmeet Kohli, Marcel van Gerven:
Deep disentangled representations for volumetric reconstruction. CoRR abs/1610.03777 (2016) - 2015
- [j26]Miguel Angel Lopez-Gordo, Daniel Sánchez Morillo, Marcel A. J. van Gerven:
Spreading Codes Enables the Blind Estimation of the Hemodynamic Response with Short-Events Sequences. Int. J. Neural Syst. 25(1): 1450035:1-1450035:12 (2015) - [j25]Irina Simanova, Marcel A. J. van Gerven, Robert Oostenveld, Peter Hagoort:
Predicting the Semantic Category of Internally Generated Words from Neuromagnetic Recordings. J. Cogn. Neurosci. 27(1): 35-45 (2015) - [j24]Haiteng Jiang, Marcel A. J. van Gerven, Ole Jensen:
Modality-specific Alpha Modulations Facilitate Long-term Memory Encoding in the Presence of Distracters. J. Cogn. Neurosci. 27(3): 583-592 (2015) - [j23]Haiteng Jiang, Ali Bahramisharif, Marcel A. J. van Gerven, Ole Jensen:
Measuring directionality between neuronal oscillations of different frequencies. NeuroImage 118: 359-367 (2015) - [j22]Ronald J. Janssen, P. Jylänki, Roy P. C. Kessels, Marcel A. J. van Gerven:
Probabilistic model-based functional parcellation reveals a robust, fine-grained subdivision of the striatum. NeuroImage 119: 398-405 (2015) - [j21]Max Hinne, Ronald J. Janssen, Tom Heskes, Marcel A. J. van Gerven:
Bayesian Estimation of Conditional Independence Graphs Improves Functional Connectivity Estimates. PLoS Comput. Biol. 11(11) (2015) - [c13]Sanne Schoenmakers, Tom Heskes, Marcel van Gerven:
Hidden Markov Models for Reading Words from the Human Brain. PRNI 2015: 89-92 - [i1]Edward Grant, Stephan Sahm, Mariam Zabihi, Marcel van Gerven:
Predicting psychological attributions from face photographs with a deep neural network. CoRR abs/1512.01289 (2015) - 2014
- [j20]Ronald J. Janssen, Max Hinne, Tom Heskes, Marcel A. J. van Gerven:
Quantifying uncertainty in brain network measures using Bayesian connectomics. Frontiers Comput. Neurosci. 8: 126 (2014) - [j19]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: 173 (2014) - [j18]Max Hinne, Luca Ambrogioni, Ronald J. Janssen, Tom Heskes, Marcel A. J. van Gerven:
Structurally-informed Bayesian functional connectivity analysis. NeuroImage 86: 294-305 (2014) - [j17]Umut Güçlü, Marcel A. J. van Gerven:
Unsupervised Feature Learning Improves Prediction of Human Brain Activity in Response to Natural Images. PLoS Comput. Biol. 10(8) (2014) - [c12]Sanne Schoenmakers, Marcel van Gerven, Tom Heskes:
Gaussian mixture models improve fMRI-based image reconstruction. PRNI 2014: 1-4 - 2013
- [j16]Diego Vidaurre, Marcel A. J. van Gerven, Concha Bielza, Pedro Larrañaga, Tom Heskes:
Bayesian Sparse Partial Least Squares. Neural Comput. 25(12): 3318-3339 (2013) - [j15]Max Hinne, Tom Heskes, Christian F. Beckmann, Marcel A. J. van Gerven:
Bayesian inference of structural brain networks. NeuroImage 66: 543-552 (2013) - [j14]Marcel A. J. van Gerven, Eric Maris, Michael R. Sperling, Ashwini Sharan, Brian Litt, Christopher Anderson, Gordon Baltuch, Joshua Jacobs:
Decoding the memorization of individual stimuli with direct human brain recordings. NeuroImage 70: 223-232 (2013) - [j13]Sanne Schoenmakers, Markus Barth, Tom Heskes, Marcel van Gerven:
Linear reconstruction of perceived images from human brain activity. NeuroImage 83: 951-961 (2013) - [j12]Marieke E. van de Nieuwenhuijzen, A. R. Backus, Ali Bahramisharif, Christian F. Doeller, Ole Jensen, Marcel A. J. van Gerven:
MEG-based decoding of the spatiotemporal dynamics of visual category perception. NeuroImage 83: 1063-1073 (2013) - 2012
- [c11]Marcel A. J. van Gerven, Tom Heskes:
A Linear Gaussian Framework for Decoding of Perceived Images. PRNI 2012: 1-4 - 2011
- [j11]Marcel van Gerven, Peter Kok, Floris P. de Lange, Tom Heskes:
Dynamic decoding of ongoing perception. NeuroImage 57(3): 950-957 (2011) - [j10]Alberto Llera, Marcel A. J. van Gerven, Vicenç Gómez, Ole Jensen, Hilbert J. Kappen:
On the use of interaction error potentials for adaptive brain computer interfaces. Neural Networks 24(10): 1120-1127 (2011) - [c10]Marcel van Gerven, Eric Maris, Tom Heskes:
A Markov Random Field Approach to Neural Encoding and Decoding. ICANN (2) 2011: 1-8 - [c9]Ali Bahramisharif, Marcel A. J. van Gerven, Jan-Mathijs Schoffelen, Zoubin Ghahramani, Tom Heskes:
The Dynamic Beamformer. MLINI 2011: 148-155 - [c8]Hans J. P. Wouters, Marcel A. J. van Gerven, Matthias Sebastian Treder, Tom Heskes, Ali Bahramisharif:
Covert Attention as a Paradigm for Subject-Independent Brain-Computer Interfacing. MLINI 2011: 156-163 - 2010
- [j9]Marcel van Gerven, Floris P. de Lange, Tom Heskes:
Neural Decoding with Hierarchical Generative Models. Neural Comput. 22(12): 3127-3142 (2010) - [j8]Marcel A. J. van Gerven, Botond Cseke, Floris P. de Lange, Tom Heskes:
Efficient Bayesian multivariate fMRI analysis using a sparsifying spatio-temporal prior. NeuroImage 50(1): 150-161 (2010) - [p1]Louis Vuurpijl, Don Willems, Ralph Niels, Marcel van Gerven:
Design Issues for Pen-Centric Interactive Maps. Interactive Collaborative Information Systems 2010: 273-297
2000 – 2009
- 2009
- [j7]Marcel van Gerven, Christian Hesse, Ole Jensen, Tom Heskes:
Interpreting single trial data using groupwise regularisation. NeuroImage 46(3): 665-676 (2009) - [j6]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): 1271-1277 (2009) - [j5]Don Willems, Ralph Niels, Marcel van Gerven, Louis Vuurpijl:
Iconic and multi-stroke gesture recognition. Pattern Recognit. 42(12): 3303-3312 (2009) - [c7]Ali Bahramisharif, Marcel van Gerven, Tom Heskes:
Exploring the impact of alternative feature representations on BCI classification. ESANN 2009 - [c6]Marcel van Gerven, Botond Cseke, Robert Oostenveld, Tom Heskes:
Bayesian Source Localization with the Multivariate Laplace Prior. NIPS 2009: 1901-1909 - 2008
- [j4]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): 214-236 (2008) - [j3]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): 515-529 (2008) - 2007
- [j2]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): 45-55 (2007) - [j1]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): 171-186 (2007) - 2006
- [c5]Marcel van Gerven, Francisco Javier Díez:
Selecting Strategies for Infinite-Horizon Dynamic LIMIDS. Probabilistic Graphical Models 2006: 131-138 - 2005
- [c4]Marcel van Gerven:
Guidelines for Probabilistic Model Qualification. BNAIC 2005: 267-274 - [c3]Marcel van Gerven, Peter J. F. Lucas, Theo P. van der Weide:
A Qualitative Characterisation of Causal Independence Models Using Boolean Polynomials. ECSQARU 2005: 244-256 - 2004
- [c2]Marcel van Gerven, Peter J. F. Lucas:
Employing Maximum Mutual Information for Bayesian Classification. ISBMDA 2004: 188-199 - [c1]Marcel van Gerven, Peter J. F. Lucas:
Using Background Knowledge to Construct Bayesian Classifiers for Data-Poor Domains. SGAI Conf. 2004: 269-282
Coauthor Index
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