Ricardo Pio Monti
Ricardo Pio Monti
Gatsby Unit, UCL
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Cited by
Cited by
Variational autoencoders and nonlinear ICA: A unifying framework
I Khemakhem, DP Kingma, RP Monti, A Hyvärinen
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Estimating time-varying brain connectivity networks from functional MRI time series
RP Monti, P Hellyer, D Sharp, R Leech, C Anagnostopoulos, G Montana
NeuroImage 103, 427-443, 2014
Causal Autoregressive Flows
I Khemakhem, RP Monti, R Leech, A Hyvärinen
The 24th International Conference on Artificial Intelligence and Statistics …, 2020
Ice-beem: Identifiable conditional energy-based deep models based on nonlinear ica
I Khemakhem, R Monti, D Kingma, A Hyvarinen
Advances in Neural Information Processing Systems 33, 12768-12778, 2020
The automatic neuroscientist: a framework for optimizing experimental design with closed-loop real-time fMRI
R Lorenz, RP Monti, IR Violante, C Anagnostopoulos, AA Faisal, ...
NeuroImage 129, 320-334, 2016
Causal Discovery with General Non-Linear Relationships Using Non-Linear ICA
RP Monti, K Zhang, A Hyvarinen
Uncertainty in Artificial Intelligence (UAI), 2019
Efficiently searching through large tACS parameter spaces using closed-loop Bayesian optimization
R Lorenz, LE Simmons, RP Monti, JL Arthur, S Limal, I Laakso, R Leech, ...
Brain stimulation 12 (6), 1484-1489, 2019
Dissociating frontoparietal brain networks with neuroadaptive Bayesian optimization
R Lorenz, IR Violante, RP Monti, G Montana, A Hampshire, R Leech
Nature communications 9 (1), 1227, 2018
Correlation between work impairment, scores of rhinitis severity and asthma using the MASK‐air® App
A Bédard, JM Antó, JA Fonseca, S Arnavielhe, C Bachert, A Bedbrook, ...
Allergy 75 (7), 1672-1688, 2020
A guided multiverse study of neuroimaging analyses
J Dafflon, P F. Da Costa, F Váša, RP Monti, D Bzdok, PJ Hellyer, ...
Nature Communications 13 (1), 3758, 2022
Stopping criteria for boosting automatic experimental design using real-time fMRI with Bayesian optimization
R Lorenz, RP Monti, IR Violante, AA Faisal, C Anagnostopoulos, R Leech, ...
5th NIPS Workshop on Machine Learning and Interpretation in Neuroimaging …, 2015
Behavioural patterns in allergic rhinitis medication in Europe: A study using MASK‐air® real‐world data
B Sousa‐Pinto, A Sá‐Sousa, RJ Vieira, R Amaral, L Klimek, W Czarlewski, ...
Allergy 77 (9), 2699-2711, 2022
Real‐time estimation of dynamic functional connectivity networks
RP Monti, R Lorenz, RM Braga, C Anagnostopoulos, R Leech, G Montana
Human brain mapping 38 (1), 202-220, 2017
Avoiding degradation in deep feed-forward networks by phasing out skip-connections
RP Monti, S Tootoonian, R Cao
International Conference on Artificial Neural Networks (ICANN) 11141, 447-456, 2018
The reference site collaborative network of the European innovation partnership on active and healthy ageing
J Bousquet, M Illario, J Farrell, N Batey, AM Carriazo, J Malva, J Hajjam, ...
Translational Medicine@ UniSa 19, 66, 2019
ICE-BeeM: Identifiable conditional energy-based deep models
I Khemakhem, DP Kingma, RP Monti, A Hyvärinen
Conference on Neural Information Processing Systems (NeurIPS 2020), 2020
Brain and behavioral alterations in subjects with social anxiety dominated by empathic embarrassment
S Tei, JP Kauppi, KF Jankowski, J Fujino, RP Monti, J Tohka, N Abe, ...
Proceedings of the National Academy of Sciences 117 (8), 4385-4391, 2020
Learning population and subject-specific brain connectivity networks via mixed neighborhood selection
RP Monti, C Anagnostopoulos, G Montana
The Annals of Applied Statistics, 2142-2164, 2017
Interpretable brain age prediction using linear latent variable models of functional connectivity
RP Monti, A Gibberd, S Roy, M Nunes, R Lorenz, R Leech, T Ogawa, ...
Plos one 15 (6), e0232296, 2020
A Unified Probabilistic Model for Learning Latent Factors and Their Connectivities from High-Dimensional Data
RP Monti, A Hyvärinen
Uncertainty in Artificial Intelligence (UAI), 2018
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