Joe Neeman
- Artificial Intelligence
- Statistical and Nonlinear Physics top 10%
- Statistics and Probability top 10%
- Computational Theory and Mathematics
- Computer Networks and Communications
- Co-authors
- Elchanan MosselAllan SlyAnindya DeSujay SanghaviInderjit S. DhillonDohyung ParkJin ZhangLorenzo Sadun
- Topics
- Markov Chains and Monte Carlo Methods (7 papers)Stochastic processes and statistical mechanics (5 papers)Machine Learning and Algorithms (4 papers)
- Journals
- IEEE Transactions on Information TheoryJournal of Machine Learning ResearchJournal of Statistical Physics
- Partner nations
- United StatesGermanyIsrael
In The Last Decade
Joe Neeman
17 papers receiving 135 citations
Peers
Comparison fields: 5 of 33
- Artificial Intelligence 61
- Statistical and Nonlinear Physics 56
- Statistics and Probability 43
- Computational Theory and Mathematics 23
- Computer Networks and Communications 22
Countries citing papers authored by Joe Neeman
This map shows the geographic impact of Joe Neeman'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 Joe Neeman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joe Neeman more than expected).
Fields of papers citing papers by Joe Neeman
This network shows the impact of papers produced by Joe Neeman. 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 Joe Neeman. The network helps show where Joe Neeman may publish in the future.
Co-authorship network of co-authors of Joe Neeman
This figure shows the co-authorship network connecting the top 25 collaborators of Joe Neeman. A scholar is included among the top collaborators of Joe Neeman 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 Joe Neeman. Joe Neeman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | Is your function low dimensional | 1 |
| 8 | The Search Problem in Mixture Models | 4 |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 0 | |
| 12 | 32 | |
| 13 | 17 | |
| 14 | 17 | |
| 15 | Consistency Thresholds for Binary Symmetric Block Models. | 24 |
| 16 | 3 | |
| 17 | 1 | |
| 18 | 3 | |
| 19 | 28 | |
| 20 | 9 |
About Joe Neeman
Joe Neeman is a scholar working on Statistics and Probability, Discrete Mathematics and Combinatorics and Computer Graphics and Computer-Aided Design, having authored 21 papers that have together received 152 indexed citations. Recurring topics across this work include Markov Chains and Monte Carlo Methods (7 papers), Stochastic processes and statistical mechanics (5 papers) and Machine Learning and Algorithms (4 papers). The work is most often cited by research in Statistics and Probability (43 citations), Statistical and Nonlinear Physics (56 citations) and Computational Mathematics (2 citations). Joe Neeman has collaborated with scholars based in United States, Germany and Israel. Frequent co-authors include Elchanan Mossel, Allan Sly, Anindya De, Sujay Sanghavi, Inderjit S. Dhillon, Dohyung Park, Jin Zhang, Lorenzo Sadun, Charles Radin and Sanjay Shakkottai. Their work appears in journals such as IEEE Transactions on Information Theory, Journal of Machine Learning Research and Journal of Statistical Physics.
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.