| 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 | 192 | 2018 |
| Theta oscillations locked to intended actions rhythmically modulate perception A Tomassini, L Ambrogioni, WP Medendorp, E Maris Elife 6, e25618, 2017 | 112 | 2017 |
| Neural dynamics of perceptual inference and its reversal during imagery N Dijkstra, L Ambrogioni, D Vidaurre, M van Gerven elife 9, e53588, 2020 | 81 | 2020 |
| Structurally-informed Bayesian functional connectivity analysis M Hinne, L Ambrogioni, RJ Janssen, T Heskes, MAJ van Gerven NeuroImage 86, 294-305, 2014 | 58 | 2014 |
| 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 | 55 | 2017 |
| Wasserstein variational inference L Ambrogioni, U Güçlü, Y Güçlütürk, M Hinne, E Maris, MAJ van Gerven Neural Information Processing Systems 2018, 2018 | 54 | 2018 |
| 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 | 49 | 2021 |
| 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, ... | 48* | |
| Gait-prop: A biologically plausible learning rule derived from backpropagation of error N Ahmad, MAJ van Gerven, L Ambrogioni Neural Information Processing Systems, 2020 | 34 | 2020 |
| 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 | 32 | 2021 |
| Brain2Pix: Fully convolutional naturalistic video frame reconstruction from brain activity L Le, L Ambrogioni, K Seeliger, Y Güç Lütürk, M Van Gerven, U Güç Lü Frontiers in Neuroscience, 1684, 0 | 28* | |
| Forward amortized inference for likelihood-free variational marginalization L Ambrogioni, U Güçlü, J Berezutskaya, E van den Borne, Y Güçlütürk, ... The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 22 | 2019 |
| Complex-valued Gaussian process regression for time series analysis L Ambrogioni, E Maris Signal Processing 160, 215-228, 2019 | 21 | 2019 |
| Spontaneous symmetry breaking in generative diffusion models G Raya, L Ambrogioni Advances in Neural Information Processing Systems 36, 2024 | 20 | 2024 |
| 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 | 17 | 2018 |
| GP CaKe: Effective brain connectivity with causal kernels L Ambrogioni, M Hinne, M Van Gerven, E Maris Neural Information Processing Systems 2017, 2017 | 16 | 2017 |
| In Search of Dispersed Memories: Generative Diffusion Models Are Associative Memory Networks L Ambrogioni Entropy 26 (5), 381, 2024 | 15 | 2024 |
| 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), 12077, 2020 | 13 | 2020 |
| Automatic variational inference with cascading flows L Ambrogioni, G Silvestri, M van Gerven International Conference on Machine Learning, 2021 | 12 | 2021 |
| Dynamic Decomposition of Spatiotemporal Neural Signals L Ambrogioni, van Gerven Marcel A.J., E Maris PLoS Computational Biology, 2016 | 12 | 2016 |
Marcel van GervenProfessor of Artificial Cognitive Systems, Donders Institute for Brain, Cognition and BehaviourVerified email at donders.ru.nl
