Tselil Schramm

690 total citations
20 papers, 143 citations indexed

About

Tselil Schramm is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Tselil Schramm has authored 20 papers receiving a total of 143 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computational Theory and Mathematics, 6 papers in Artificial Intelligence and 4 papers in Computer Networks and Communications. Recurrent topics in Tselil Schramm's work include Complexity and Algorithms in Graphs (8 papers), Advanced Graph Theory Research (6 papers) and Sparse and Compressive Sensing Techniques (3 papers). Tselil Schramm is often cited by papers focused on Complexity and Algorithms in Graphs (8 papers), Advanced Graph Theory Research (6 papers) and Sparse and Compressive Sensing Techniques (3 papers). Tselil Schramm collaborates with scholars based in United States, Israel and United Kingdom. Tselil Schramm's co-authors include David Steurer, Alexander S. Wein, Samuel B. Hopkins, Jonathan Shi, Prasad Raghavendra, Shuchi Chawla, Konstantin Makarychev, Grigory Yaroslavtsev, Satish Rao and Varun Kanade and has published in prestigious journals such as IEEE Transactions on Information Theory, The Annals of Statistics and SIAM Journal on Computing.

In The Last Decade

Tselil Schramm

18 papers receiving 139 citations

Peers

Countries citing papers authored by Tselil Schramm

Since Specialization

Citations

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

Fields of papers citing papers by Tselil Schramm

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tselil Schramm

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	Discrepancy Algorithms for the Binary Perceptron 2025 ·(unknown), Tselil Schramm, Kangjie Zhou	0
2	Testing Thresholds for High-Dimensional Sparse Random Geometric Graphs 2024 ·SIAM Journal on Computing ·Siqi Liu, (unknown), Tselil Schramm, (unknown)	1
3	Semidefinite Programs Simulate Approximate Message Passing Robustly 2024 ·(unknown), Tselil Schramm	1
4	Local and Global Expansion in Random Geometric Graphs 2023 ·Siqi Liu, (unknown), Tselil Schramm, (unknown)	3
5	The Franz-Parisi Criterion and Computational Trade-Offs in High Dimensional Statistics 2022 ·Afonso S. Bandeira, (unknown), Samuel B. Hopkins, Tselil Schramm, Alexander S. Wein, (unknown)	0
6	Computational barriers to estimation from low-degree polynomials 2022 ·The Annals of Statistics ·Tselil Schramm, Alexander S. Wein	21
7	2021 ·Theory of Computing ·Ryan O’Donnell, Tselil Schramm	1
8	Sherali - Adams Strikes Back 2019 ·DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) ·Ryan O’Donnell, Tselil Schramm	2
9	Nearly) Efficient Algorithms for the Graph Matching Problem on Correlated Random Graphs 2018 ·arXiv (Cornell University) ·Boaz Barak, (unknown), (unknown), Tselil Schramm, (unknown)	8
10	On the Integrality Gap of Degree-4 Sum of Squares for Planted Clique 2018 ·ACM Transactions on Algorithms ·Samuel B. Hopkins, Pravesh K. Kothari, (unknown), Prasad Raghavendra, Tselil Schramm	4
11	Computing Exact Minimum Cuts Without Knowing the Graph 2018 ·DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) ·Aviad Rubinstein, Tselil Schramm, S. Matthew Weinberg	3
12	Strongly refuting random CSPs below the spectral threshold 2017 ·Prasad Raghavendra, Satish Rao, Tselil Schramm	15
13	Fast and robust tensor decomposition with applications to dictionary learning. 2017 ·Tselil Schramm, David Steurer	5
14	Braess's paradox for the spectral gap in random graphs and delocalization of eigenvectors 2016 ·Random Structures and Algorithms ·Ronen Eldan, Miklós Z. Rácz, Tselil Schramm	7
15	Global and Local Information in Clustering Labeled Block Models 2016 ·IEEE Transactions on Information Theory ·Varun Kanade, Elchanan Mossel, Tselil Schramm	7
16	Fast spectral algorithms from sum-of-squares proofs: tensor decomposition and planted sparse vectors 2016 ·Samuel B. Hopkins, Tselil Schramm, Jonathan Shi, David Steurer	37
17	On the Integrality Gap of Degree-4 Sum of Squares for Planted Clique 2015 ·Samuel B. Hopkins, Pravesh K. Kothari, (unknown), Prasad Raghavendra, Tselil Schramm	1
18	Near Optimal LP Rounding Algorithm for CorrelationClustering on Complete and Complete k-partite Graphs 2015 ·Shuchi Chawla, Konstantin Makarychev, Tselil Schramm, Grigory Yaroslavtsev	24
19	Global and Local Information in Clustering Labeled Block Models 2014 ·arXiv (Cornell University) ·Varun Kanade, Elchanan Mossel, Tselil Schramm	2
20	Gap Amplification for Small-Set Expansion via Random Walks 2014 ·DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) ·Prasad Raghavendra, Tselil Schramm	1

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.

Explore authors with similar magnitude of impact