Ronen Eldan
Impact in
- Statistics and Probability top 5%
- Markov Chains and Monte Carlo Methods
- Statistical Methods and Inference
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- Limits and Structures in Graph Theory
Papers in
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- Markov Chains and Monte Carlo Methods 15
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- Bayesian Methods and Mixture Models 4
- Machine Learning and Algorithms 3
- Bayesian Modeling and Causal Inference 3
- Co-authors
- Ohad Shamir (1 shared paper)Joseph Lehec (5 shared papers)Sébastien Bubeck (4 shared papers)Yuansi Chen (3 shared papers)Bo’az Klartag (1 shared paper)James R. Lee (3 shared papers)Alex Zhai (2 shared papers)Jian Ding (2 shared papers)
- Journals
- Lecture notes in mathematics (3 papers)Duke Mathematical Journal (2 papers)Geometric and Functional Analysis (2 papers)Annales de l Institut Henri Poincaré Probabilités et Statistiques (2 papers)The Annals of Probability (2 papers)
- Partner nations
- IsraelUnited StatesFrance
In The Last Decade
Ronen Eldan
30 papers receiving 454 citations
Peers
Comparison fields: 5 of 71
- Statistics and Probability 138
- Discrete Mathematics and Combinatorics 48
- Applied Mathematics 145
- Mathematical Physics 91
- Geometry and Topology 47
Countries citing papers authored by Ronen Eldan
This map shows the geographic impact of Ronen Eldan'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 Ronen Eldan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ronen Eldan more than expected).
Fields of papers citing papers by Ronen Eldan
This network shows the impact of papers produced by Ronen Eldan. 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 Ronen Eldan. The network helps show where Ronen Eldan may publish in the future.
Co-authors
The 17 scholars most cited alongside Ronen Eldan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | The Power of Depth for Feedforward Neural Networks | 2016 | 144 |
| 2 | 2013 | 58 | |
| 3 | 2018 | 35 | |
| 4 | 2014 | 34 | |
| 5 | 2015 | 31 | |
| 6 | 2022 | 25 | |
| 7 | 2014 | 20 | |
| 8 | 2008 | 19 | |
| 9 | 2018 | 11 | |
| 10 | 2017 | 11 | |
| 11 | 2015 | 10 | |
| 12 | 2014 | 8 | |
| 13 | 2020 | 7 | |
| 14 | The entropic barrier: a simple and optimal universal self-concordant barrier | 2015 | 7 |
| 15 | 2016 | 7 | |
| 16 | Bandit smooth convex optimization: improving the bias-variance tradeoff | 2015 | 5 |
| 17 | Finite-time analysis of projected Langevin Monte Carlo | 2015 | 5 |
| 18 | 2022 | 5 | |
| 19 | 2022 | 5 | |
| 20 | 2023 | 5 |
About Ronen Eldan
Ronen Eldan is a scholar working on Statistics and Probability, Artificial Intelligence, Applied Mathematics, Mathematical Physics and Computational Theory and Mathematics, having authored 34 papers that have together received 478 indexed citations. Recurring topics across this work include Markov Chains and Monte Carlo Methods (15 papers), Point processes and geometric inequalities (7 papers), Stochastic processes and statistical mechanics (7 papers), Geometric Analysis and Curvature Flows (4 papers), Bayesian Methods and Mixture Models (4 papers), Stochastic processes and financial applications (3 papers), Machine Learning and Algorithms (3 papers) and Bayesian Modeling and Causal Inference (3 papers). The work is most often cited by research in Statistics and Probability (138 citations), Discrete Mathematics and Combinatorics (48 citations), Applied Mathematics (145 citations), Mathematical Physics (91 citations) and Geometry and Topology (47 citations). Ronen Eldan has collaborated with scholars based in Israel, United States and France. Frequent co-authors include Ohad Shamir, Joseph Lehec, Sébastien Bubeck, Yuansi Chen, Bo’az Klartag, James R. Lee, Alex Zhai, Jian Ding, Tomer Koren and Itaï Benjamini. Their work appears in journals such as Lecture notes in mathematics, Duke Mathematical Journal, Geometric and Functional Analysis, Annales de l Institut Henri Poincaré Probabilités et Statistiques and The Annals of Probability.
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.