Jasmine Collins

1.0k total citations · 1 hit paper
6 papers, 419 citations indexed

About

Jasmine Collins is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Jasmine Collins has authored 6 papers receiving a total of 419 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Computer Vision and Pattern Recognition, 1 paper in Molecular Biology and 1 paper in Cellular and Molecular Neuroscience. Recurrent topics in Jasmine Collins's work include Neural dynamics and brain function (1 paper), Protein Structure and Dynamics (1 paper) and Neural Networks and Applications (1 paper). Jasmine Collins is often cited by papers focused on Neural dynamics and brain function (1 paper), Protein Structure and Dynamics (1 paper) and Neural Networks and Applications (1 paper). Jasmine Collins collaborates with scholars based in United States, India and Germany. Jasmine Collins's co-authors include David Sussillo, Rafał Józefowicz, Eric M. Trautmann, Leigh R. Hochberg, Sergey D. Stavisky, Stephen I. Ryu, Krishna V. Shenoy, L. F. Abbott, Chethan Pandarinath and Daniel J. O’Shea and has published in prestigious journals such as Nature Methods, Cognitive Science and Journal of Computer-Aided Molecular Design.

In The Last Decade

Jasmine Collins

6 papers receiving 415 citations

Hit Papers

align trajectories

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.

Inferring single-trial neural population dynamics using sequential auto-encoders

2018 306 citations Chethan Pandarinath, Daniel J. O’Shea et al. Nature Methods profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jasmine Collins United States	4	275	101	97	64	53	6	419
Zhikai Chen China	11	266 1.0×	148 1.5×	193 2.0×	228 3.6×	80 1.5×	24	663
Mulugeta Semework United States	6	123 0.4×	131 1.3×	60 0.6×	72 1.1×	17 0.3×	14	391
Toru Aonishi Japan	12	201 0.7×	129 1.3×	118 1.2×	30 0.5×	61 1.2×	52	436
John Choi United States	7	86 0.3×	141 1.4×	34 0.4×	75 1.2×	27 0.5×	15	356
Martin Rehn Sweden	9	259 0.9×	120 1.2×	83 0.9×	80 1.3×	140 2.6×	14	410
Benjamin D. Haeffele United States	7	149 0.5×	61 0.6×	105 1.1×	52 0.8×	21 0.4×	22	327
Morteza Alamgir Germany	7	342 1.2×	80 0.8×	122 1.3×	35 0.5×	99 1.9×	10	481
Bernhard Schoelkopf Germany	11	147 0.5×	237 2.3×	84 0.9×	90 1.4×	19 0.4×	19	483
Benjamin Lansdell United States	7	150 0.5×	84 0.8×	68 0.7×	34 0.5×	50 0.9×	11	293
Shreya Saxena United States	10	260 0.9×	60 0.6×	114 1.2×	19 0.3×	35 0.7×	25	368

Countries citing papers authored by Jasmine Collins

Since Specialization

Citations

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

Fields of papers citing papers by Jasmine Collins

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jasmine Collins

This figure shows the co-authorship network connecting the top 25 collaborators of Jasmine Collins. A scholar is included among the top collaborators of Jasmine Collins 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 Jasmine Collins. Jasmine Collins 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:

6 of 6 papers shown

1.

Gokaslan, Aaron, A. Feder Cooper, Jasmine Collins, et al.. (2024). Common Canvas: Open Diffusion Models Trained on Creative-Commons Images. 8250–8260. 1 indexed citations

2.

Collins, Jasmine, Shubham Goel, Erhan Gündoğdu, et al.. (2022). ABO: Dataset and Benchmarks for Real-World 3D Object Understanding. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 21094–21104. 61 indexed citations

3.

Collins, Jasmine, et al.. (2020). Exploring Exploration: Comparing Children with Agents in Unified Exploration Environments.. Cognitive Science. 1 indexed citations

4.

Pandarinath, Chethan, Daniel J. O’Shea, Jasmine Collins, et al.. (2018). Inferring single-trial neural population dynamics using sequential auto-encoders. Nature Methods. 15(10). 805–815. 306 indexed citations breakdown →

5.

Sunseri, Jocelyn, Matthew Ragoza, Jasmine Collins, & David Ryan Koes. (2016). A D3R prospective evaluation of machine learning for protein-ligand scoring. Journal of Computer-Aided Molecular Design. 30(9). 761–771. 13 indexed citations

6.

Collins, Jasmine, Jascha Sohl‐Dickstein, & David Sussillo. (2016). Capacity and Trainability in Recurrent Neural Networks. arXiv (Cornell University). 37 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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