Rodrigo Echeveste

414 total citations
9 papers, 201 citations indexed

About

Rodrigo Echeveste is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Rodrigo Echeveste has authored 9 papers receiving a total of 201 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cognitive Neuroscience, 4 papers in Artificial Intelligence and 1 paper in Computer Networks and Communications. Recurrent topics in Rodrigo Echeveste's work include Neural dynamics and brain function (7 papers), Neural Networks and Applications (2 papers) and Visual perception and processing mechanisms (2 papers). Rodrigo Echeveste is often cited by papers focused on Neural dynamics and brain function (7 papers), Neural Networks and Applications (2 papers) and Visual perception and processing mechanisms (2 papers). Rodrigo Echeveste collaborates with scholars based in Argentina, United Kingdom and Germany. Rodrigo Echeveste's co-authors include Enzo Ferrante, Máté Lengyel, Laurence Aitchison, Guillaume Hennequin, Claudius Gros, Mark Kotter, John S. O’Neill, Inés Samengo and Diego H. Milone and has published in prestigious journals such as Nature Communications, Nature Neuroscience and PLoS ONE.

In The Last Decade

Rodrigo Echeveste

9 papers receiving 197 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rodrigo Echeveste Argentina 5 78 55 50 48 27 9 201
Catalina Gómez United States 8 87 1.1× 106 1.9× 80 1.6× 65 1.4× 7 0.3× 19 333
Gopal Sarma United States 6 43 0.6× 48 0.9× 12 0.2× 21 0.4× 16 0.6× 17 268
Po‐Chih Kuo Taiwan 10 100 1.3× 41 0.7× 15 0.3× 72 1.5× 16 0.6× 36 264
Yiming Ding United Kingdom 6 38 0.5× 136 2.5× 47 0.9× 150 3.1× 5 0.2× 8 440
J. F. Esteban Müller Switzerland 4 113 1.4× 26 0.5× 5 0.1× 17 0.4× 43 1.6× 5 200
Soorena Salari Iran 5 178 2.3× 51 0.9× 17 0.3× 52 1.1× 5 0.2× 7 286
Yogatheesan Varatharajah United States 10 240 3.1× 35 0.6× 11 0.2× 26 0.5× 70 2.6× 24 328
Ari S. Benjamin United States 6 106 1.4× 40 0.7× 5 0.1× 8 0.2× 30 1.1× 6 218
Amanda LeBel United States 4 126 1.6× 25 0.5× 7 0.1× 11 0.2× 10 0.4× 5 188
Shailee Jain United States 5 138 1.8× 43 0.8× 7 0.1× 7 0.1× 9 0.3× 9 208

Countries citing papers authored by Rodrigo Echeveste

Since Specialization
Citations

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

Fields of papers citing papers by Rodrigo Echeveste

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rodrigo Echeveste

This figure shows the co-authorship network connecting the top 25 collaborators of Rodrigo Echeveste. A scholar is included among the top collaborators of Rodrigo Echeveste 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 Rodrigo Echeveste. Rodrigo Echeveste is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Echeveste, Rodrigo, et al.. (2022). Addressing fairness in artificial intelligence for medical imaging. Nature Communications. 13(1). 4581–4581. 107 indexed citations
2.
Echeveste, Rodrigo, Enzo Ferrante, Diego H. Milone, & Inés Samengo. (2021). Bridging physiological and perceptual views of autism by means of sampling-based Bayesian inference. Network Neuroscience. 6(1). 196–212. 1 indexed citations
3.
Echeveste, Rodrigo, Laurence Aitchison, Guillaume Hennequin, & Máté Lengyel. (2020). Cortical-like dynamics in recurrent circuits optimized for sampling-based probabilistic inference. Nature Neuroscience. 23(9). 1138–1149. 63 indexed citations
4.
Echeveste, Rodrigo, et al.. (2019). Energetic substrate availability regulates synchronous activity in an excitatory neural network. PLoS ONE. 14(8). e0220937–e0220937. 11 indexed citations
5.
Echeveste, Rodrigo, et al.. (2019). The subjective metric of remembered colors: A Fisher-information analysis of the geometry of human chromatic memory. PLoS ONE. 14(1). e0207992–e0207992. 2 indexed citations
6.
Echeveste, Rodrigo & Máté Lengyel. (2018). The Redemption of Noise: Inference with Neural Populations. Trends in Neurosciences. 41(11). 767–770. 5 indexed citations
7.
Echeveste, Rodrigo, et al.. (2018). E-I balance emerges naturally from continuous Hebbian learning in autonomous neural networks. Scientific Reports. 8(1). 8939–8939. 7 indexed citations
8.
Echeveste, Rodrigo & Claudius Gros. (2016). Drifting States and Synchronization Induced Chaos in Autonomous Networks of Excitable Neurons. Frontiers in Computational Neuroscience. 10. 98–98. 3 indexed citations
9.
Echeveste, Rodrigo, et al.. (2015). The Fisher Information as a Neural Guiding Principle for Independent Component Analysis. Entropy. 17(6). 3838–3856. 2 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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