Elad Eban

1.1k total citations
11 papers, 501 citations indexed

About

Elad Eban is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Elad Eban has authored 11 papers receiving a total of 501 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Signal Processing. Recurrent topics in Elad Eban's work include Machine Learning and Data Classification (3 papers), Bayesian Modeling and Causal Inference (2 papers) and Time Series Analysis and Forecasting (2 papers). Elad Eban is often cited by papers focused on Machine Learning and Data Classification (3 papers), Bayesian Modeling and Causal Inference (2 papers) and Time Series Analysis and Forecasting (2 papers). Elad Eban collaborates with scholars based in Israel, United States and Italy. Elad Eban's co-authors include Gideon Rothschild, Loren M. Frank, Ariel Gordon, Bo Chen, Hao Wu, Edward Choi, Ofir Nachum, Tien-Ju Yang, Dorit Aharonov and Michael Ben-Or and has published in prestigious journals such as Nature Neuroscience, ArXiv.org and arXiv (Cornell University).

In The Last Decade

Elad Eban

10 papers receiving 485 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Elad Eban Israel	6	249	156	152	129	31	11	501
Gopathy Purushothaman United States	11	592 2.4×	189 1.2×	183 1.2×	57 0.4×	34 1.1×	21	843
Grace W. Lindsay United States	7	505 2.0×	159 1.0×	149 1.0×	135 1.0×	57 1.8×	11	838
Yoichi Miyawaki Japan	10	730 2.9×	68 0.4×	88 0.6×	130 1.0×	79 2.5×	25	886
Dahlia Sharon Israel	9	507 2.0×	238 1.5×	31 0.2×	130 1.0×	28 0.9×	11	821
Mulugeta Semework United States	6	123 0.5×	60 0.4×	131 0.9×	72 0.6×	6 0.2×	14	391
Risto Miikkulainen United States	14	439 1.8×	129 0.8×	175 1.2×	103 0.8×	33 1.1×	23	598
Richard Romero United States	7	634 2.5×	81 0.5×	64 0.4×	139 1.1×	66 2.1×	10	810
Benjamin D. Haeffele United States	7	149 0.6×	105 0.7×	61 0.4×	52 0.4×	10 0.3×	22	327
Andrea Banino United Kingdom	6	200 0.8×	47 0.3×	128 0.8×	107 0.8×	29 0.9×	7	405
Atsunori Kanemura Japan	12	212 0.9×	55 0.4×	42 0.3×	133 1.0×	37 1.2×	43	473

Countries citing papers authored by Elad Eban

Since Specialization

Citations

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

Fields of papers citing papers by Elad Eban

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Elad Eban

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

All Works

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11 of 11 papers shown

1.

Liba, Orly, Yair Movshovitz-Attias, Yael Pritch, et al.. (2020). Sky Optimization: Semantically aware image processing of skies in low-light photography. 2230–2238. 11 indexed citations

2.

Gordon, Ariel, Elad Eban, Ofir Nachum, et al.. (2018). MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks. 1586–1595. 159 indexed citations

3.

Livni, Roi, et al.. (2016). Improper Deep Kernels. International Conference on Artificial Intelligence and Statistics. 1159–1167.

4.

Eban, Elad, et al.. (2016). Scalable Learning of Non-Decomposable Objectives. International Conference on Artificial Intelligence and Statistics. 832–840. 15 indexed citations

5.

Rothschild, Gideon, Elad Eban, & Loren M. Frank. (2016). A cortical–hippocampal–cortical loop of information processing during memory consolidation. Nature Neuroscience. 20(2). 251–259. 262 indexed citations

6.

Eban, Elad, et al.. (2014). Discrete Chebyshev Classifiers. International Conference on Machine Learning. 1233–1241. 5 indexed citations

7.

El‐Hay, Tal, Omer Weissbrod, Elad Eban, Maurizio Zazzi, & Francesca Incardona. (2014). Structured proportional jump processes. 172–181. 1 indexed citations

8.

Eban, Elad, Gideon Rothschild, Adi Mizrahi, Israel Nelken, & Gal Elidan. (2013). Dynamic Copula Networks for Modeling Real-valued Time Series. International Conference on Artificial Intelligence and Statistics. 247–255. 8 indexed citations

9.

Meshi, Ofer, Elad Eban, Gal Elidan, & Amir Globerson. (2013). Learning Max-Margin Tree Predictors. arXiv (Cornell University). 411–420. 1 indexed citations

10.

Aharonov, Dorit, Itai Arad, Elad Eban, & Zeph Landau. (2008). Polynomial Quantum algorithms for additive approximations of the Potts model and other points of the Tutte plane Preliminary Version. 1 indexed citations

11.

Aharonov, Dorit, et al.. (2008). Interactive Proofs For Quantum Computations. ArXiv.org. 453–469. 38 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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