Elad Schneidman
- Cognitive Neuroscience top 0.5%
- Cellular and Molecular Neuroscience top 1%
- Statistical and Nonlinear Physics top 0.5%
- Molecular Biology top 10%
- Artificial Intelligence top 2%
- Co-authors
- Michael J. BerryWilliam BialekRonen SegevIdan SegevBarry FreedmanGašper TkačikElad GanmorJason Puchalla
- Topics
- Neural dynamics and brain function (33 papers)Neural Networks and Applications (12 papers)Neuroscience and Neural Engineering (10 papers)
- Partner nations
- IsraelUnited StatesAustria
In The Last Decade
Elad Schneidman
49 papers receiving 3.7k citations
Hit Papers
Peers
Comparison fields: 5 of 138
- Cognitive Neuroscience 2.4k
- Cellular and Molecular Neuroscience 1.3k
- Statistical and Nonlinear Physics 814
- Molecular Biology 769
- Artificial Intelligence 493
Countries citing papers authored by Elad Schneidman
This map shows the geographic impact of Elad Schneidman'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 Elad Schneidman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Elad Schneidman more than expected).
Fields of papers citing papers by Elad Schneidman
This network shows the impact of papers produced by Elad Schneidman. 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 Elad Schneidman. The network helps show where Elad Schneidman may publish in the future.
Co-authorship network of co-authors of Elad Schneidman
This figure shows the co-authorship network connecting the top 25 collaborators of Elad Schneidman. A scholar is included among the top collaborators of Elad Schneidman 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 Elad Schneidman. Elad Schneidman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 18 | |
| 5 | 8 | |
| 6 | 19 | |
| 7 | 25 | |
| 8 | 2 | |
| 9 | 80 | |
| 10 | 150 | |
| 11 | 64 | |
| 12 | 52 | |
| 13 | 50 | |
| 14 | 57 | |
| 15 | 63 | |
| 16 | 72 | |
| 17 | Weak pairwise correlations imply strongly correlated network states in a neural populationbreakdown → | 1100 |
| 18 | 191 | |
| 19 | 42 | |
| 20 | Information Capacity and Robustness of Stochastic Neuron Models | 22 |
About Elad Schneidman
Elad Schneidman is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Aging, having authored 51 papers that have together received 3.8k indexed citations. Recurring topics across this work include Neural dynamics and brain function (33 papers), Neural Networks and Applications (12 papers) and Neuroscience and Neural Engineering (10 papers). The work is most often cited by research in Cognitive Neuroscience (2.4k citations), Cellular and Molecular Neuroscience (1.3k citations) and Statistical and Nonlinear Physics (814 citations). Elad Schneidman has collaborated with scholars based in Israel, United States and Austria. Frequent co-authors include Michael J. Berry, William Bialek, Ronen Segev, Idan Segev, Barry Freedman, Gašper Tkačik, Elad Ganmor, Jason Puchalla, Susanne Still and R. Adron Harris. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Physical Review Letters.
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.