| A survey on multi‐output regression H Borchani, G Varando, C Bielza, P Larranaga Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 5 (5 …, 2015 | 736 | 2015 |
| Causal inference for time series J Runge, A Gerhardus, G Varando, V Eyring, G Camps-Valls Nature Reviews Earth & Environment 4 (7), 487-505, 2023 | 127 | 2023 |
| Discovering causal relations and equations from data G Camps-Valls, A Gerhardus, U Ninad, G Varando, G Martius, ... Physics Reports 1044, 1-68, 2023 | 54 | 2023 |
| Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values S Weichwald, ME Jakobsen, PB Mogensen, L Petersen, N Thams, ... NeurIPS 2019 Competition and Demonstration Track, 27-36, 2020 | 37 | 2020 |
| The R package stagedtrees for structural learning of stratified staged trees F Carli, M Leonelli, E Riccomagno, G Varando Journal of Statistical Software 102 (6), 1-30, 2022 | 32 | 2022 |
| Decision boundary for discrete Bayesian network classifiers G Varando, MC Bielza Lozoya, PM Larrañaga Múgica Journal of Machine Learning Research, 2725-2749, 2015 | 32 | 2015 |
| Graphical continuous Lyapunov models G Varando, NR Hansen Conference on Uncertainty in Artificial Intelligence, 989-998, 2020 | 20 | 2020 |
| Decision functions for chain classifiers based on Bayesian networks for multi-label classification G Varando, C Bielza, P Larrañaga International Journal of Approximate Reasoning 68, 164-178, 2016 | 17 | 2016 |
| Context-specific causal discovery for categorical data using staged trees M Leonelli, G Varando International conference on artificial intelligence and statistics, 8871-8888, 2023 | 16 | 2023 |
| Highly efficient structural learning of sparse staged trees M Leonelli, G Varando International conference on probabilistic graphical models, 193-204, 2022 | 15 | 2022 |
| Staged trees and asymmetry-labeled DAGs G Varando, F Carli, M Leonelli Metrika, 1-28, 2024 | 12 | 2024 |
| A new class of generative classifiers based on staged tree models F Carli, M Leonelli, G Varando Knowledge-Based Systems 268, 110488, 2023 | 12 | 2023 |
| Structural learning of simple staged trees M Leonelli, G Varando Data Mining and Knowledge Discovery, 1-25, 2024 | 11 | 2024 |
| On generating random Gaussian graphical models I Córdoba, G Varando, C Bielza, P Larrañaga International Journal of Approximate Reasoning 125, 240-250, 2020 | 11 | 2020 |
| Learning DAGs without imposing acyclicity G Varando arXiv preprint arXiv:2006.03005, 2020 | 11 | 2020 |
| Expressive power of binary relevance and chain classifiers based on Bayesian networks for multi-label classification G Varando, C Bielza, P Larranaga Probabilistic Graphical Models: 7th European Workshop, PGM 2014, Utrecht …, 2014 | 11 | 2014 |
| MultiMap: a tool to automatically extract and analyse spatial microscopic data from large stacks of confocal microscopy images G Varando, R Benavides-Piccione, A Muñoz, A Kastanauskaite, C Bielza, ... Frontiers in Neuroanatomy 12, 37, 2018 | 9 | 2018 |
| Large Language Models for Constrained-Based Causal Discovery KH Cohrs, G Varando, E Diaz, V Sitokonstantinou, G Camps-Valls arXiv preprint arXiv:2406.07378, 2024 | 7 | 2024 |
| Learning Granger Causal Feature Representations G Varando, MA Fernández-Torres, G Camps-Valls | 7 | 2021 |
| Learning and interpreting asymmetry-labeled DAGs: a case study on COVID-19 fear M Leonelli, G Varando Applied Intelligence 54 (2), 1734-1750, 2024 | 6 | 2024 |
Pedro LarrañagaProfessor of Artificial Intelligence - Universidad Politécnica de MadridVerified email at fi.upm.es