P.F. Verdes

1.3k total citations
27 papers, 1000 citations indexed

About

P.F. Verdes is a scholar working on Artificial Intelligence, Signal Processing and Statistical and Nonlinear Physics. According to data from OpenAlex, P.F. Verdes has authored 27 papers receiving a total of 1000 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 7 papers in Signal Processing and 6 papers in Statistical and Nonlinear Physics. Recurrent topics in P.F. Verdes's work include Neural Networks and Applications (8 papers), Time Series Analysis and Forecasting (7 papers) and Complex Systems and Time Series Analysis (5 papers). P.F. Verdes is often cited by papers focused on Neural Networks and Applications (8 papers), Time Series Analysis and Forecasting (7 papers) and Complex Systems and Time Series Analysis (5 papers). P.F. Verdes collaborates with scholars based in Argentina, Germany and Austria. P.F. Verdes's co-authors include Pablo M. Granitto, H. A. Ceccatto, Christoph Spötl, Augusto Mangini, H. D. Navone, Lucas C. Uzal, Guillermo L. Grinblat, Denis Scholz, Bernd Kromer and Rubén D. Piacentini and has published in prestigious journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Earth and Planetary Science Letters.

In The Last Decade

P.F. Verdes

27 papers receiving 925 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
P.F. Verdes Argentina 15 328 193 176 147 117 27 1000
Andy Gardiner United Kingdom 9 318 1.0× 51 0.3× 150 0.9× 17 0.1× 322 2.8× 15 1.3k
Robert Moorhead United States 22 287 0.9× 58 0.3× 156 0.9× 26 0.2× 162 1.4× 122 1.7k
Guo Guo 18 145 0.4× 94 0.5× 173 1.0× 6 0.0× 130 1.1× 232 1.1k
Yan 15 60 0.2× 110 0.6× 189 1.1× 19 0.1× 58 0.5× 405 1.3k
Yuehua Wu Canada 21 363 1.1× 37 0.2× 193 1.1× 14 0.1× 510 4.4× 125 1.7k
Nicholas M. Short United States 21 234 0.7× 136 0.7× 116 0.7× 12 0.1× 65 0.6× 60 1.1k
Alina Zare United States 26 616 1.9× 234 1.2× 393 2.2× 288 2.0× 156 1.3× 154 2.5k
Yang Shao United States 24 351 1.1× 90 0.5× 597 3.4× 57 0.4× 472 4.0× 74 2.4k
Claudio Agostinelli Italy 17 201 0.6× 14 0.1× 120 0.7× 32 0.2× 113 1.0× 57 1.0k
Vineet Kumar India 16 236 0.7× 179 0.9× 40 0.2× 43 0.3× 152 1.3× 57 1.1k

Countries citing papers authored by P.F. Verdes

Since Specialization
Citations

This map shows the geographic impact of P.F. Verdes's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by P.F. Verdes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites P.F. Verdes more than expected).

Fields of papers citing papers by P.F. Verdes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by P.F. Verdes. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by P.F. Verdes. The network helps show where P.F. Verdes may publish in the future.

Co-authorship network of co-authors of P.F. Verdes

This figure shows the co-authorship network connecting the top 25 collaborators of P.F. Verdes. A scholar is included among the top collaborators of P.F. Verdes based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with P.F. Verdes. P.F. Verdes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Grinblat, Guillermo L., Lucas C. Uzal, P.F. Verdes, & Pablo M. Granitto. (2014). Nonstationary regression with support vector machines. Neural Computing and Applications. 26(3). 641–649. 15 indexed citations
2.
Uzal, Lucas C., Rubén D. Piacentini, & P.F. Verdes. (2012). Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24. Solar Physics. 279(2). 551–560. 10 indexed citations
3.
Uzal, Lucas C., Guillermo L. Grinblat, & P.F. Verdes. (2011). Optimal reconstruction of dynamical systems: A noise amplification approach. Physical Review E. 84(1). 16223–16223. 28 indexed citations
4.
Verdes, P.F.. (2007). Global Warming Is Driven by Anthropogenic Emissions: A Time Series Analysis Approach. Physical Review Letters. 99(4). 48501–48501. 24 indexed citations
5.
Mangini, Augusto, et al.. (2007). Combined records from a stalagmite from Barbados and from lake sediments in Haiti reveal variable seasonality in the Caribbean between 6.7 and 3 ka BP. Quaternary Science Reviews. 26(9-10). 1332–1343. 25 indexed citations
6.
Verdes, P.F., Pablo M. Granitto, & H. A. Ceccatto. (2006). Overembedding Method for Modeling Nonstationary Systems. Physical Review Letters. 96(11). 118701–118701. 17 indexed citations
7.
Verdes, P.F.. (2005). Assessing causality from multivariate time series. Physical Review E. 72(2). 26222–26222. 98 indexed citations
8.
Mangini, Augusto, Christoph Spötl, & P.F. Verdes. (2005). Reconstruction of temperature in the Central Alps during the past 2000 yr from a δ18O stalagmite record. Earth and Planetary Science Letters. 235(3-4). 741–751. 224 indexed citations
9.
Granitto, Pablo M., P.F. Verdes, & H. A. Ceccatto. (2004). Neural network ensembles: evaluation of aggregation algorithms. Artificial Intelligence. 163(2). 139–162. 129 indexed citations
10.
Verdes, P.F., Pablo M. Granitto, & H. A. Ceccatto. (2004). Secular Behavior of Solar Magnetic Activity: Nonstationary Time-Series Analysis of the Sunspot Record. Solar Physics. 221(1). 167–177. 6 indexed citations
11.
Verdes, P.F., et al.. (2003). Artificial Neural Network Learning of Nonstationary Behavior in Time Series. International Journal of Neural Systems. 13(2). 103–109. 10 indexed citations
12.
Granitto, Pablo M., et al.. (2003). Boosting classifiers for weed seeds identification. SHILAP Revista de lepidopterología. 3(1). 34–39. 22 indexed citations
13.
Verdes, P.F., et al.. (2003). Modelling nonstationary dynamics. Physica A Statistical Mechanics and its Applications. 327(1-2). 190–194. 10 indexed citations
14.
Granitto, Pablo M., H. D. Navone, P.F. Verdes, & H. A. Ceccatto. (2002). Weed seeds identification by machine vision. Computers and Electronics in Agriculture. 33(2). 91–103. 111 indexed citations
15.
Navone, H. D., P.F. Verdes, Pablo M. Granitto, & H. A. Ceccatto. (2002). Selecting diverse members of neural network ensembles. 255–260. 12 indexed citations
16.
Navone, H. D., et al.. (2001). A Learning Algorithm For Neural Network Ensembles. INTELIGENCIA ARTIFICIAL. 5(12). 16 indexed citations
17.
Verdes, P.F., Pablo M. Granitto, H. D. Navone, & H. A. Ceccatto. (2001). Nonstationary Time-Series Analysis: Accurate Reconstruction of Driving Forces. Physical Review Letters. 87(12). 124101–124101. 36 indexed citations
18.
Granitto, Pablo M., P.F. Verdes, H. D. Navone, & H. A. Ceccatto. (2001). A LATE-STOPPING METHOD FOR OPTIMAL AGGREGATION OF NEURAL NETWORKS. International Journal of Neural Systems. 11(3). 305–310. 7 indexed citations
19.
Granitto, Pablo M., et al.. (2000). Automatic identification of weed seeds by color image processing. El Servicio de Difusión de la Creación Intelectual (National University of La Plata). 12 indexed citations
20.
Verdes, P.F., et al.. (2000). Frost prediction with machine learning techniques. El Servicio de Difusión de la Creación Intelectual (National University of La Plata). 10 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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