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Scaling up learning with GAIT-prop


Feb 23, 2021
Sander Dalm, Nasir Ahmad, Luca Ambrogioni, Marcel van Gerven


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Automatic variational inference with cascading flows


Feb 09, 2021
Luca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven


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GAIT-prop: A biologically plausible learning rule derived from backpropagation of error


Jul 01, 2020
Nasir Ahmad, Marcel A. J. van Gerven, Luca Ambrogioni

* 12 pages, 4 figures 

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Explainable 3D Convolutional Neural Networks by Learning Temporal Transformations


Jun 29, 2020
Gabriëlle Ras, Luca Ambrogioni, Pim Haselager, Marcel A. J. van Gerven, Umut Güçlü

* 10 pages, 5 figures, 4 tables 

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Spike-Timing-Dependent Inference of Synaptic Weights


Mar 09, 2020
Nasir Ahmad, Luca Ambrogioni, Marcel A. J. van Gerven

* 19 pages, 6 figures 

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Automatic structured variational inference


Feb 03, 2020
Luca Ambrogioni, Max Hinne, Marcel van Gerven


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The Indian Chefs Process


Jan 29, 2020
Patrick Dallaire, Luca Ambrogioni, Ludovic Trottier, Umut Güçlü, Max Hinne, Philippe Giguère, Brahim Chaib-Draa, Marcel van Gerven, Francois Laviolette


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Background Hardly Matters: Understanding Personality Attribution in Deep Residual Networks


Dec 20, 2019
Gabriëlle Ras, Ron Dotsch, Luca Ambrogioni, Umut Güçlü, Marcel A. J. van Gerven

* 10 pages, 4 figures, 2 tables 

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Temporal Factorization of 3D Convolutional Kernels


Dec 09, 2019
Gabriëlle Ras, Luca Ambrogioni, Umut Güçlü, Marcel A. J. van Gerven

* 8 pages, 3 figures, Proceedings of BNAIC/BENELEARN 2019 conference 

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Causal inference using Bayesian non-parametric quasi-experimental design


Nov 15, 2019
Max Hinne, Marcel A. J. van Gerven, Luca Ambrogioni

* 20 pages, 8 figures 

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k-GANs: Ensemble of Generative Models with Semi-Discrete Optimal Transport


Jul 09, 2019
Luca Ambrogioni, Umut Güçlü, Marcel van Gerven


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Perturbative estimation of stochastic gradients


Apr 08, 2019
Luca Ambrogioni, Marcel A. J. van Gerven


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Wasserstein Variational Gradient Descent: From Semi-Discrete Optimal Transport to Ensemble Variational Inference


Nov 07, 2018
Luca Ambrogioni, Umut Guclu, Yagmur Gucluturk, Marcel van Gerven


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Wasserstein Variational Inference


Jun 04, 2018
Luca Ambrogioni, Umut Güçlü, Yağmur Güçlütürk, Max Hinne, Eric Maris, Marcel A. J. van Gerven

* 8 pages, 1 figure 

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Forward Amortized Inference for Likelihood-Free Variational Marginalization


May 29, 2018
Luca Ambrogioni, Umut Güçlü, Julia Berezutskaya, Eva W. P. van den Borne, Yağmur Güçlütürk, Max Hinne, Eric Maris, Marcel A. J. van Gerven

* 9 pages, 3 figures 

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Complex-valued Gaussian Process Regression for Time Series Analysis


Dec 07, 2017
Luca Ambrogioni, Eric Maris


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Integral Transforms from Finite Data: An Application of Gaussian Process Regression to Fourier Analysis


Dec 06, 2017
Luca Ambrogioni, Eric Maris


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The Kernel Mixture Network: A Nonparametric Method for Conditional Density Estimation of Continuous Random Variables


May 19, 2017
Luca Ambrogioni, Umut Güçlü, Marcel A. J. van Gerven, Eric Maris


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GP CaKe: Effective brain connectivity with causal kernels


May 16, 2017
Luca Ambrogioni, Max Hinne, Marcel van Gerven, Eric Maris


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Estimating Nonlinear Dynamics with the ConvNet Smoother


Apr 21, 2017
Luca Ambrogioni, Umut Güçlü, Eric Maris, Marcel van Gerven


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Analysis of Nonstationary Time Series Using Locally Coupled Gaussian Processes


Oct 31, 2016
Luca Ambrogioni, Eric Maris


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Dynamic Decomposition of Spatiotemporal Neural Signals


May 09, 2016
Luca Ambrogioni, Marcel A. J. van Gerven, Eric Maris


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