Ricardo Pio Monti

According to our database, Ricardo Pio Monti authored at least 22 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2023

Identifiability of latent-variable and structural-equation models: from linear to nonlinear.

Aapo Hyvärinen, Ilyes Khemakhem, Ricardo Pio Monti

CoRR, 2023

2022

Controllable Generative Modeling via Causal Reasoning.

Joey Bose, Ricardo Pio Monti, Aditya Grover

Trans. Mach. Learn. Res., 2022

2021

Causal Autoregressive Flows.

Ilyes Khemakhem, Ricardo Pio Monti, Robert Leech, Aapo Hyvärinen

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Bayesian optimization for automatic design of face stimuli.

Pedro F. Da Costa, Romy Lorenz, Ricardo Pio Monti, Emily J. H. Jones, Robert Leech

CoRR, 2020

Autoregressive flow-based causal discovery and inference.

Ricardo Pio Monti, Ilyes Khemakhem, Aapo Hyvärinen

CoRR, 2020

ICE-BeeM: Identifiable Conditional Energy-Based Deep Models.

Ilyes Khemakhem, Ricardo Pio Monti, Diederik P. Kingma, Aapo Hyvärinen

CoRR, 2020

Robust contrastive learning and nonlinear ICA in the presence of outliers.

Hiroaki Sasaki, Takashi Takenouchi, Ricardo Pio Monti, Aapo Hyvärinen

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA.

Ilyes Khemakhem, Ricardo Pio Monti, Diederik P. Kingma, Aapo Hyvärinen

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Variational Autoencoders and Nonlinear ICA: A Unifying Framework.

Ilyes Khemakhem, Diederik P. Kingma, Ricardo Pio Monti, Aapo Hyvärinen

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Towards the interpretation of time-varying regularization parameters in streaming penalized regression models.

Lenka Zbonáková, Ricardo Pio Monti, Wolfgang Karl Härdle

Pattern Recognit. Lett., 2019

Causal Discovery with General Non-Linear Relationships using Non-Linear ICA.

Ricardo Pio Monti, Kun Zhang, Aapo Hyvärinen

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

2018

Adaptive regularization for Lasso models in the context of nonstationary data streams.

Ricardo Pio Monti, Christoforos Anagnostopoulos, Giovanni Montana

Stat. Anal. Data Min., 2018

A unified probabilistic model for learning latent factors and their connectivities from high-dimensional data .

Ricardo Pio Monti, Aapo Hyvärinen

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Avoiding Degradation in Deep Feed-Forward Networks by Phasing Out Skip-Connections.

Ricardo Pio Monti, Sina Tootoonian, Robin Cao

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

2017

Decoding Time-Varying Functional Connectivity Networks via Linear Graph Embedding Methods.

Ricardo Pio Monti, Romy Lorenz, Peter Hellyer, Robert Leech, Christoforos Anagnostopoulos, Giovanni Montana

Frontiers Comput. Neurosci., 2017

2016

The Automatic Neuroscientist: A framework for optimizing experimental design with closed-loop real-time fMRI.

Romy Lorenz, Ricardo Pio Monti, Inês R. Violante, Christoforos Anagnostopoulos, Aldo A. Faisal, Giovanni Montana, Robert Leech

NeuroImage, 2016

A framework for adaptive regularization in streaming Lasso models.

Ricardo Pio Monti, Christoforos Anagnostopoulos, Giovanni Montana

CoRR, 2016

Text-mining the neurosynth corpus using deep boltzmann machines.

Ricardo Pio Monti, Romy Lorenz, Robert Leech, Christoforos Anagnostopoulos, Giovanni Montana

Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2016

Towards tailoring non-invasive brain stimulation using real-time fMRI and Bayesian optimization.

Romy Lorenz, Ricardo Pio Monti, Adam Hampshire, Yury Koush, Christoforos Anagnostopoulos, Aldo A. Faisal, David J. Sharp, Giovanni Montana, Robert Leech, Inês R. Violante

Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2016

Classifying HCP task-fMRI networks using heat kernels.

Ai Wern Chung, Emanuele Pesce, Ricardo Pio Monti, Giovanni Montana

Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2016

2015

Graph Embeddings of Dynamic Functional Connectivity Reveal Discriminative Patterns of Task Engagement in HCP Data.

Ricardo Pio Monti, Romy Lorenz, Peter Hellyer, Robert Leech, Christoforos Anagnostopoulos, Giovanni Montana

Proceedings of the 2015 International Workshop on Pattern Recognition in NeuroImaging, 2015

2014

Estimating time-varying brain connectivity networks from functional MRI time series.

Ricardo Pio Monti, Peter Hellyer, David J. Sharp, Robert Leech, Christoforos Anagnostopoulos, Giovanni Montana

NeuroImage, 2014