Pietro Berkes
- Cognitive Neuroscience top 2%
- Artificial Intelligence top 5%
- Cellular and Molecular Neuroscience top 5%
- Electrical and Electronic Engineering
- Signal Processing top 5%
- Co-authors
- József FiserMáté LengyelGergő OrbánLaurenz WiskottRalf M. HaefnerRichard E. TurnerManeesh SahaniMathias Franzius
- Topics
- Neural dynamics and brain function (14 papers)Visual perception and processing mechanisms (8 papers)Advanced Fluorescence Microscopy Techniques (5 papers)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Pietro Berkes
19 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 96
- Cognitive Neuroscience 1.2k
- Artificial Intelligence 295
- Cellular and Molecular Neuroscience 286
- Electrical and Electronic Engineering 177
- Signal Processing 143
Countries citing papers authored by Pietro Berkes
This map shows the geographic impact of Pietro Berkes'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 Pietro Berkes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pietro Berkes more than expected).
Fields of papers citing papers by Pietro Berkes
This network shows the impact of papers produced by Pietro Berkes. 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 Pietro Berkes. The network helps show where Pietro Berkes may publish in the future.
Co-authorship network of co-authors of Pietro Berkes
This figure shows the co-authorship network connecting the top 25 collaborators of Pietro Berkes. A scholar is included among the top collaborators of Pietro Berkes 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 Pietro Berkes. Pietro Berkes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Discovering Customer Journey Maps using a Mixture of Markov Models. | 2 |
| 2 | 141 | |
| 3 | 118 | |
| 4 | 1 | |
| 5 | Probabilistic computation: A possible functional role for spontaneous activity in the cortex | 2 |
| 6 | Select and Sample - A Model of Efficient Neural Inference and Learning | 11 |
| 7 | 3 | |
| 8 | 40 | |
| 9 | 475 | |
| 10 | 444 | |
| 11 | No evidence for active sparsification in the visual cortex | 18 |
| 12 | 29 | |
| 13 | Characterizing neural dependencies with copula models | 25 |
| 14 | 5 | |
| 15 | On Sparsity and Overcompleteness in Image Models | 12 |
| 16 | 55 | |
| 17 | 182 | |
| 18 | Pattern Recognition with Slow Feature Analysis | 30 |
| 19 | 10 |
About Pietro Berkes
Pietro Berkes is a scholar working on Biophysics, Cognitive Neuroscience and Signal Processing, having authored 19 papers that have together received 1.6k indexed citations. Recurring topics across this work include Neural dynamics and brain function (14 papers), Visual perception and processing mechanisms (8 papers) and Advanced Fluorescence Microscopy Techniques (5 papers). The work is most often cited by research in Cognitive Neuroscience (1.2k citations), General Decision Sciences (46 citations) and Cellular and Molecular Neuroscience (286 citations). Pietro Berkes has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include József Fiser, Máté Lengyel, Gergő Orbán, Laurenz Wiskott, Ralf M. Haefner, Richard E. Turner, Maneesh Sahani, Mathias Franzius, Henning Sprekeler and Jonathan W. Pillow. Their work appears in journals such as Science, Neuron and Trends in Cognitive Sciences.
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.