Nestor Caticha

829 total citations
57 papers, 490 citations indexed

About

Nestor Caticha is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Condensed Matter Physics. According to data from OpenAlex, Nestor Caticha has authored 57 papers receiving a total of 490 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Artificial Intelligence, 17 papers in Statistical and Nonlinear Physics and 11 papers in Condensed Matter Physics. Recurrent topics in Nestor Caticha's work include Neural Networks and Applications (20 papers), Machine Learning and Algorithms (11 papers) and Theoretical and Computational Physics (8 papers). Nestor Caticha is often cited by papers focused on Neural Networks and Applications (20 papers), Machine Learning and Algorithms (11 papers) and Theoretical and Computational Physics (8 papers). Nestor Caticha collaborates with scholars based in Brazil, United Kingdom and United States. Nestor Caticha's co-authors include Osame Kinouchi, Renato Vicente, Mauro Copelli, Marcus Vinícius C. Baldo, Vitor B. P. Leite, Jorge Chahine, J. R. Drugowich de Felício, Ariel Caticha, Marcelo Boareto and André C. R. Martins and has published in prestigious journals such as SHILAP Revista de lepidopterología, Physical review. B, Condensed matter and Applied Physics Letters.

In The Last Decade

Nestor Caticha

53 papers receiving 472 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nestor Caticha Brazil 12 253 166 76 73 52 57 490
S. Diederich Germany 8 174 0.7× 89 0.5× 23 0.3× 74 1.0× 63 1.2× 15 375
Andreas Engel Germany 5 167 0.7× 90 0.5× 38 0.5× 73 1.0× 35 0.7× 7 350
Susanne Still United States 14 255 1.0× 273 1.6× 38 0.5× 270 3.7× 22 0.4× 27 846
Amin Vahdat United States 5 180 0.7× 431 2.6× 28 0.4× 36 0.5× 40 0.8× 6 743
Ying-Cheng Lai United States 9 73 0.3× 373 2.2× 20 0.3× 121 1.7× 19 0.4× 9 576
Ruedi Stoop Switzerland 17 141 0.6× 354 2.1× 24 0.3× 290 4.0× 72 1.4× 83 898
Zoran Levnajić Slovenia 13 75 0.3× 282 1.7× 17 0.2× 159 2.2× 12 0.2× 31 636
Daniele Tantari Italy 12 164 0.6× 168 1.0× 7 0.1× 96 1.3× 105 2.0× 31 431
Peter beim Graben Germany 18 230 0.9× 208 1.3× 37 0.5× 470 6.4× 7 0.1× 52 774
Barry Cipra United States 11 102 0.4× 123 0.7× 9 0.1× 27 0.4× 58 1.1× 101 616

Countries citing papers authored by Nestor Caticha

Since Specialization
Citations

This map shows the geographic impact of Nestor Caticha'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 Nestor Caticha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nestor Caticha more than expected).

Fields of papers citing papers by Nestor Caticha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nestor Caticha. 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 Nestor Caticha. The network helps show where Nestor Caticha may publish in the future.

Co-authorship network of co-authors of Nestor Caticha

This figure shows the co-authorship network connecting the top 25 collaborators of Nestor Caticha. A scholar is included among the top collaborators of Nestor Caticha 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 Nestor Caticha. Nestor Caticha 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.
Caticha, Nestor, et al.. (2024). Statistical Mechanics of Social Hierarchies: A Mathematical Model for the Evolution of Human Societal Structures. Physics. 6(2). 629–644. 1 indexed citations
2.
Neirotti, Juan Pablo & Nestor Caticha. (2024). Legislative rebellions and impeachments in a neural network society. Physical review. E. 110(5). 54110–54110. 1 indexed citations
3.
Caticha, Nestor, et al.. (2023). Interacting dreaming neural networks. Journal of Statistical Mechanics Theory and Experiment. 2023(4). 43401–43401.
4.
Caticha, Nestor, et al.. (2019). Trust, law and ideology in a NN agent model of the US Appellate Courts.. The European Symposium on Artificial Neural Networks. 2 indexed citations
5.
Baccalá, Luiz Antonio, et al.. (2017). Backward renormalization-group inference of cortical dipole sources and neural connectivity efficacy. Physical review. E. 95(6). 62415–62415.
6.
Caticha, Nestor, et al.. (2017). Exploration and recency as the main proximate causes of probability matching: a reinforcement learning analysis. Scientific Reports. 7(1). 15326–15326. 6 indexed citations
7.
Schonmann, Roberto H., Renato Vicente, & Nestor Caticha. (2013). Altruism Can Proliferate through Population Viscosity despite High Random Gene Flow. PLoS ONE. 8(8). e72043–e72043. 11 indexed citations
8.
Boareto, Marcelo, M. E. B. Yamagishi, Nestor Caticha, & Vitor B. P. Leite. (2012). Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction. Computational Biology and Chemistry. 40. 15–19. 7 indexed citations
9.
Caticha, Nestor, et al.. (2010). Inference From Aging Information. IEEE Transactions on Neural Networks. 21(6). 1015–1020. 5 indexed citations
10.
Ribeiro, Fabiano L. & Nestor Caticha. (2008). Emergence and loss of assortative mating in sympatric speciation. Journal of Theoretical Biology. 258(3). 465–477. 9 indexed citations
11.
Caticha, Nestor, et al.. (2008). Emergence of sensory selection mechanisms in Artificial Life simulations. BMC Neuroscience. 9(S1). 1 indexed citations
12.
Caticha, Nestor & Juan Pablo Neirotti. (2006). The evolution of learning systems: to Bayes or not to be. AIP conference proceedings. 872. 203–210. 1 indexed citations
13.
Caticha, Nestor, et al.. (2006). BOLD response analysis by iterated local multigrid priors. NeuroImage. 36(2). 361–369. 5 indexed citations
14.
Caticha, Nestor, et al.. (2004). Multigrid priors for a Bayesian approach to fMRI. NeuroImage. 23(2). 654–662. 8 indexed citations
15.
Neirotti, Juan Pablo, et al.. (2003). Superparamagnetic segmentation by excitable neural systems. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 68(3). 31911–31911. 2 indexed citations
16.
Neirotti, Juan Pablo & Nestor Caticha. (2003). Dynamics of the evolution of learning algorithms by selection. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 67(4). 41912–41912. 5 indexed citations
17.
Caticha, Nestor, et al.. (2001). Gradient descent learning in and out of equilibrium. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 63(6). 61905–61905. 4 indexed citations
18.
Kinouchi, Osame, et al.. (1998). Learning a spin glass: Determining Hamiltonians from metastable states. Physica A Statistical Mechanics and its Applications. 257(1-4). 28–35. 3 indexed citations
19.
Copelli, Mauro, et al.. (1997). Noise robustness in multilayer neural networks. Europhysics Letters (EPL). 37(6). 427–432. 11 indexed citations
20.
Chahine, Jorge, J. R. Drugowich de Felício, & Nestor Caticha. (1989). Using the Ferrenberg-Swendsen Monte Carlo method for nonuniversal exponents. Physics Letters A. 139(8). 360–362. 1 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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