12 citations · 13 across the 6 of their papers we have counts for
6 papers
Debiasing the Lasso under Weaker Tail Assumptions
Leonardo Voltarelli, Roberto Imbuzeiro Oliveira
We consider the problem of high-dimensional inference with the lasso estimator. Different methods including 'double selection' techniques and multiple versions of the 'debiased las…
Interpretable liquid crystal phase classification via two-by-two ordinal patterns
Leonardo G. J. M. Voltarelli, Natalia Osiecka-Drewniak, Marcin Piwowarczyk +4
Liquid crystal textures encode rich structural information, yet mapping these images to mesophase identity remains challenging because visually similar patterns can arise from dist…
Precipitation nowcasting of satellite data using physically-aligned neural networks
Antônio Catão, Melvin Poveda, Leonardo Voltarelli +1
Accurate short-term precipitation forecasts predominantly rely on dense weather-radar networks, limiting operational value in places most exposed to climate extremes. We present TU…
Similarity networks of ordinal-pattern transitions classify falling paper trajectories
Angelo A. Flores, Leonardo G. J. M. Voltarelli, Andre S. Sunahara +2
Paper fragments in free fall constitute a simple yet paradigmatic mechanical system exhibiting remarkably complex motions. Despite a long history of investigation, this system has…
Nearest neighbor permutation entropy detects phase transitions in complex high-pressure systems
Arthur A. B. Pessa, Leonardo G. J. M. Voltarelli, Lucio Cardozo-Filho +5
Understanding the high-pressure phase behavior of carbon dioxide-hydrocarbon mixtures is of considerable interest owing to their wide range of applications. Under certain condition…
Characterizing unstructured data with the nearest neighbor permutation entropy
Leonardo G. J. M. Voltarelli, Arthur A. B. Pessa, Luciano Zunino +4
Permutation entropy and its associated frameworks are remarkable examples of physics-inspired techniques adept at processing complex and extensive datasets. Despite substantial pro…