Follow
Luca Ambrogioni
Luca Ambrogioni
Donder's institute of Cognition
Verified email at donders.ru.nl
Title
Cited by
Cited by
Year
Generative adversarial networks for reconstructing natural images from brain activity
K Seeliger, U Güçlü, L Ambrogioni, Y Güçlütürk, MAJ van Gerven
NeuroImage 181, 775-785, 2018
892018
Theta oscillations locked to intended actions rhythmically modulate perception
A Tomassini, L Ambrogioni, WP Medendorp, E Maris
Elife 6, e25618, 2017
732017
Structurally-informed Bayesian functional connectivity analysis
M Hinne, L Ambrogioni, RJ Janssen, T Heskes, MAJ van Gerven
NeuroImage 86, 294-305, 2014
472014
Wasserstein variational inference
L Ambrogioni, U Güçlü, Y Güçlütürk, M Hinne, E Maris, MAJ van Gerven
Neural Information Processing Systems 2018, 2018
332018
Neural dynamics of perceptual inference and its reversal during imagery
N Dijkstra, L Ambrogioni, D Vidaurre, M van Gerven
Elife 9, e53588, 2020
242020
The kernel mixture network: A nonparametric method for conditional density estimation of continuous random variables
L Ambrogioni, U Güçlü, MAJ van Gerven, E Maris
arXiv preprint arXiv:1705.07111, 2017
242017
End-to-end neural system identification with neural information flow
K Seeliger, L Ambrogioni, Y Güçlütürk, LM van den Bulk, U Güçlü, ...
PLOS Computational Biology 17 (2), e1008558, 2021
172021
Gait-prop: A biologically plausible learning rule derived from backpropagation of error
N Ahmad, MAJ van Gerven, L Ambrogioni
Neural Information Processing Systems, 2020
132020
GP CaKe: Effective brain connectivity with causal kernels
L Ambrogioni, M Hinne, M Van Gerven, E Maris
Neural Information Processing Systems 2017, 2017
132017
Complex-valued Gaussian process regression for time series analysis
L Ambrogioni, E Maris
Signal Processing 160, 215-228, 2019
122019
Wasserstein variational gradient descent: From semi-discrete optimal transport to ensemble variational inference
L Ambrogioni, U Guclu, M van Gerven
Bayesian Deep Learning workshop. NeurIPS, 2018
102018
Dynamic Decomposition of Spatiotemporal Neural Signals
L Ambrogioni, van Gerven Marcel A.J., E Maris
PLoS Computational Biology, 2016
82016
Automatic structured variational inference
L Ambrogioni, K Lin, E Fertig, S Vikram, M Hinne, D Moore, M van Gerven
International Conference on Artificial Intelligence and Statistics, 676-684, 2021
72021
Estimating nonlinear dynamics with the ConvNet smoother
L Ambrogioni, U Güçlü, E Maris, M van Gerven
arXiv preprint arXiv:1702.05243, 2017
62017
Automatic variational inference with cascading flows
L Ambrogioni, G Silvestri, M van Gerven
International Conference on Machine Learning, 2021
42021
Brain2Pix: Fully convolutional naturalistic video reconstruction from brain activity
L Le, L Ambrogioni, K Seeliger, Y Güçlütürk, M van Gerven, U Güçlü
BioRxiv, 2021
42021
DeepRF: Ultrafast population receptive field mapping with deep learning
J Thielen, U Güçlü, Y Güçlütürk, L Ambrogioni, SE Bosch, ...
bioRxiv, 732990, 2019
42019
Integral Transforms from Finite Data: An Application of Gaussian Process Regression to Fourier Analysis
L Ambrogioni, E Maris
International Conference on Artificial Intelligence and Statistics, 217-225, 2018
42018
Hyperrealistic neural decoding: Reconstruction of face stimuli from fMRI measurements via the GAN latent space
T Dado, Y Güçlütürk, L Ambrogioni, G Ras, SE Bosch, M van Gerven, ...
32020
Cortical network responses map onto data-driven features that capture visual semantics of movie fragments
J Berezutskaya, ZV Freudenburg, L Ambrogioni, U Güçlü, ...
Scientific reports 10 (1), 1-21, 2020
32020
The system can't perform the operation now. Try again later.
Articles 1–20