Ricardo Pio Monti | DeepAI

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Featured Co-authors

Kun Zhang
106 publications
Giovanni Montana
48 publications
Aapo Hyvärinen
42 publications
Diederik P. Kingma
21 publications
Wolfgang Karl Härdle
21 publications
Christoforos Anagnostopoulos
11 publications
Robert Leech
9 publications
Romy Lorenz
6 publications
Alex Gibberd
6 publications
Ilyes Khemakhem
6 publications
Pedro F. da Costa
5 publications

∙ 11/04/2020

Causal Autoregressive Flows

Two apparently unrelated fields – normalizing flows and causality – have...

0 Ilyes Khemakhem, et al. ∙

∙ 09/25/2020

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

High-dimensional, streaming datasets are ubiquitous in modern applicatio...

0 Lenka Zboňáková, et al. ∙

∙ 07/20/2020

Bayesian optimization for automatic design of face stimuli

Investigating the cognitive and neural mechanisms involved with face pro...

0 Pedro F. da Costa, et al. ∙

∙ 07/18/2020

Autoregressive flow-based causal discovery and inference

We posit that autoregressive flow models are well-suited to performing a...

0 Ricardo Pio Monti, et al. ∙

∙ 02/26/2020

ICE-BeeM: Identifiable Conditional Energy-Based Deep Models

Despite the growing popularity of energy-based models, their identifiabi...

6 Ilyes Khemakhem, et al. ∙

∙ 08/05/2019

Interpretable brain age prediction using linear latent variable models of functional connectivity

Neuroimaging-driven prediction of brain age, defined as the predicted bi...

0 Ricardo Pio Monti, et al. ∙

∙ 04/19/2019

Causal Discovery with General Non-Linear Relationships Using Non-Linear ICA

We consider the problem of inferring causal relationships between two or...

0 Ricardo Pio Monti, et al. ∙

∙ 05/24/2018

A Unified Probabilistic Model for Learning Latent Factors and Their Connectivities from High-Dimensional Data

Connectivity estimation is challenging in the context of high-dimensiona...

0 Ricardo Pio Monti, et al. ∙

∙ 10/28/2016

Adaptive regularization for Lasso models in the context of non-stationary data streams

Large scale, streaming datasets are ubiquitous in modern machine learnin...

0 Ricardo Pio Monti, et al. ∙

∙ 05/01/2016

Text-mining the NeuroSynth corpus using Deep Boltzmann Machines

Large-scale automated meta-analysis of neuroimaging data has recently es...

0 Ricardo Pio Monti, et al. ∙

∙ 12/07/2015

Learning population and subject-specific brain connectivity networks via Mixed Neighborhood Selection

In neuroimaging data analysis, Gaussian graphical models are often used ...

0 Ricardo Pio Monti, et al. ∙

∙ 11/06/2015

Streaming regularization parameter selection via stochastic gradient descent

We propose a framework to perform streaming covariance selection. Our ap...

0 Ricardo Pio Monti, et al. ∙

∙ 02/08/2015

Measuring the functional connectome "on-the-fly": towards a new control signal for fMRI-based brain-computer interfaces

There has been an explosion of interest in functional Magnetic Resonance...

0 Ricardo Pio Monti, et al. ∙

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