Avraham Ruderman

1.5k total citations · 1 hit paper
5 papers, 371 citations indexed

About

Avraham Ruderman is a scholar working on Artificial Intelligence, Statistics and Probability and Computer Vision and Pattern Recognition. According to data from OpenAlex, Avraham Ruderman has authored 5 papers receiving a total of 371 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 2 papers in Statistics and Probability and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in Avraham Ruderman's work include Statistical Methods and Inference (2 papers), Advanced Statistical Methods and Models (1 paper) and Statistical Distribution Estimation and Applications (1 paper). Avraham Ruderman is often cited by papers focused on Statistical Methods and Inference (2 papers), Advanced Statistical Methods and Models (1 paper) and Statistical Distribution Estimation and Applications (1 paper). Avraham Ruderman collaborates with scholars based in Australia and United Kingdom. Avraham Ruderman's co-authors include Neil C. Rabinowitz, Ari S. Morcos, Charles Beattie, Joel Z. Leibo, David Silver, Luke Marris, Demis Hassabis, Tim Green, Antonio García Castañeda and Guy Lever and has published in prestigious journals such as Science, Journal of Statistical Planning and Inference and arXiv (Cornell University).

In The Last Decade

Avraham Ruderman

5 papers receiving 360 citations

Hit Papers

Human-level performance in 3D multiplayer games with popu... 2019 2026 2021 2023 2019 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Human-level performance in 3D multiplayer games with population-based reinforcement learning
    2019 349 citations Max Jaderberg, Wojciech Marian Czarnecki et al. Science profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Avraham Ruderman Australia 4 246 58 42 37 37 5 371
Antonio García Castañeda United Kingdom 4 241 1.0× 102 1.8× 44 1.0× 42 1.1× 39 1.1× 5 439
Gregory Kuhlmann United States 8 354 1.4× 61 1.1× 49 1.2× 33 0.9× 31 0.8× 10 423
István Szita Hungary 8 416 1.7× 51 0.9× 64 1.5× 76 2.1× 28 0.8× 18 544
Vinícius Zambaldi United Kingdom 7 285 1.2× 39 0.7× 46 1.1× 44 1.2× 84 2.3× 8 393
Alan Blair Australia 13 412 1.7× 84 1.4× 21 0.5× 30 0.8× 21 0.6× 48 583
Tengfei Shi China 7 187 0.8× 69 1.2× 25 0.6× 16 0.4× 49 1.3× 15 323
Bei Shi China 11 606 2.5× 87 1.5× 29 0.7× 29 0.8× 40 1.1× 22 723
Christoph Dann United States 8 189 0.8× 47 0.8× 21 0.5× 54 1.5× 31 0.8× 14 406
Harm van Seijen Canada 8 186 0.8× 34 0.6× 45 1.1× 33 0.9× 38 1.0× 17 294
Aaron Wilson United States 9 250 1.0× 49 0.8× 41 1.0× 47 1.3× 33 0.9× 16 427

Countries citing papers authored by Avraham Ruderman

Since Specialization
Citations

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

Fields of papers citing papers by Avraham Ruderman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Avraham Ruderman

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

All Works

5 of 5 papers shown
1.
Jaderberg, Max, Wojciech Marian Czarnecki, Iain Dunning, et al.. (2019). Human-level performance in 3D multiplayer games with population-based reinforcement learning. Science. 364(6443). 859–865. 349 indexed citations breakdown →
2.
Ruderman, Avraham, Neil C. Rabinowitz, Ari S. Morcos, & Daniel Zoran. (2018). Learned Deformation Stability in Convolutional Neural Networks.. arXiv (Cornell University). 6 indexed citations
3.
Ruderman, Avraham, Richard Everett, Hubert Soyer, et al.. (2018). Uncovering Surprising Behaviors in Reinforcement Learning via Worst-case Analysis. 6 indexed citations
4.
Ruderman, Avraham, et al.. (2012). Tighter Variational Representations of f-Divergences via Restriction to Probability Measures. arXiv (Cornell University). 1155–1162. 8 indexed citations
5.
Penev, Spiridon & Avraham Ruderman. (2010). On the behaviour of tests based on sample spacings for moderatesamples. Journal of Statistical Planning and Inference. 141(3). 1240–1249. 2 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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