Scholar
Ricardo Pio Monti
Google Scholar ID: ppYWVlYAAAAJ
Gatsby Unit, UCL
Citations & Impact
Citations
2,305
H-index
20
i10-index
23
Publications
20
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- Publications:
- - Variational autoencoders and Nonlinear ICA: A Unifying Framework (AISTATS 2020)
- - Interpretable brain age prediction using linear latent variable models of functional connectivity (PLOS ONE)
- - Causal discovery with general non-linear relationships using non-linear ica (UAI 2019)
- - Learning population and subject-specific brain connectivity networks via mixed neighborhood selection (The Annals of Applied Statistics, 2017)
- - A unified probabilistic model for learning latent factors and their connectivities from high-dimensional data (UAI 2018)
- - Adaptive regularization for Lasso models in the context of non-stationary data streams (Statistical Analysis and Data Mining, 2018)
- - The automatic neuroscientist: a framework for optimizing experimental design with closed-loop real-time fMRI (NeuroImage, 2016)
Research Experience
- Postdoc: Gatsby Computational Neuroscience Unit, UCL, working with Aapo Hyvärinen.
Education
- PhD: Statistics Department, Imperial College London, Supervisors: Christoforos Anagnostopoulos and Giovanni Montana.
Background
- Currently a postdoc at the Gatsby Computational Neuroscience Unit, UCL, working with Aapo Hyvärinen. Prior to this, completed a PhD in the Statistics Department at Imperial College London, supervised by Christoforos Anagnostopoulos and Giovanni Montana.
Co-authors