Sara Sabour

1.6k total citations · 1 hit paper
5 papers, 462 citations indexed

About

Sara Sabour is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Artificial Intelligence. According to data from OpenAlex, Sara Sabour has authored 5 papers receiving a total of 462 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computer Vision and Pattern Recognition, 2 papers in Computational Mechanics and 2 papers in Artificial Intelligence. Recurrent topics in Sara Sabour's work include Computer Graphics and Visualization Techniques (2 papers), Adversarial Robustness in Machine Learning (2 papers) and 3D Shape Modeling and Analysis (2 papers). Sara Sabour is often cited by papers focused on Computer Graphics and Visualization Techniques (2 papers), Adversarial Robustness in Machine Learning (2 papers) and 3D Shape Modeling and Analysis (2 papers). Sara Sabour collaborates with scholars based in United States, Canada and Germany. Sara Sabour's co-authors include Geoffrey E. Hinton, Nicholas Frosst, Andrea Tagliasacchi, Daniel Duckworth, Ivan Krasin, David J. Fleet, Animesh Garg, Yao Qin, Garrison W. Cottrell and Colin Raffel and has published in prestigious journals such as ACM Transactions on Graphics, arXiv (Cornell University) and International Conference on Learning Representations.

In The Last Decade

Sara Sabour

5 papers receiving 438 citations

Hit Papers

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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.

Matrix capsules with EM routing

2018 406 citations Geoffrey E. Hinton, Sara Sabour et al. International Conference on Learning Representations profile →

Peers

Countries citing papers authored by Sara Sabour

Since Specialization

Citations

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

Fields of papers citing papers by Sara Sabour

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sara Sabour

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

All Works

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5 of 5 papers shown

#	Work	Indexed citations
1	SpotLessSplats: Ignoring Distractors in 3D Gaussian Splatting 2025 ·ACM Transactions on Graphics ·Sara Sabour, (unknown), Georgios Kopanas, Mark A. Matthews, Dmitry Lagun, Leonidas Guibas, Alec Jacobson, David J. Fleet, Andrea Tagliasacchi	4
2	RobustNeRF: Ignoring Distractors with Robust Losses 2023 ·Sara Sabour, (unknown), Daniel Duckworth, Ivan Krasin, David J. Fleet, Andrea Tagliasacchi	29
3	nerf2nerf: Pairwise Registration of Neural Radiance Fields 2023 ·(unknown), (unknown), Sara Sabour, Animesh Garg, Andrea Tagliasacchi	16
4	Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions 2020 ·arXiv (Cornell University) ·Yao Qin, Nicholas Frosst, Sara Sabour, Colin Raffel, Garrison W. Cottrell, Geoffrey E. Hinton	7
5	Matrix capsules with EM routing breakdown → 2018 ·International Conference on Learning Representations ·Geoffrey E. Hinton, Sara Sabour, Nicholas Frosst	406

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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