Paroma Varma

3.1k total citations · 1 hit paper
19 papers, 1.3k citations indexed

About

Paroma Varma is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Biophysics. According to data from OpenAlex, Paroma Varma has authored 19 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 3 papers in Biophysics. Recurrent topics in Paroma Varma's work include Machine Learning and Data Classification (5 papers), Multimodal Machine Learning Applications (4 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Paroma Varma is often cited by papers focused on Machine Learning and Data Classification (5 papers), Multimodal Machine Learning Applications (4 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Paroma Varma collaborates with scholars based in United States, India and United Kingdom. Paroma Varma's co-authors include Bradley Voytek, Avgusta Y. Shestyuk, Robert T. Knight, Torben Noto, Thomas Donoghue, Joni D. Wallis, Antonio H. Lara, Erik Peterson, Richard Gao and Christopher Ré and has published in prestigious journals such as Nature Communications, Nature Neuroscience and Proceedings of the VLDB Endowment.

In The Last Decade

Paroma Varma

17 papers receiving 1.3k 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.

Parameterizing neural power spectra into periodic and aperiodic components

2020 1.0k citations Thomas Donoghue, Erik Peterson et al. Nature Neuroscience profile →

Peers

Paroma Varma

CN

CMN

AI

NEURO

CVPR

Okito Yamashita Japan

Francisco Gómez Colombia

Anahita Adeli United States

Gan Huang China

Christian Rummel Switzerland

Shreya Bhat India

Ardalan Aarabi France

Nikolaos Laskaris Greece

Xi Luo United States

Frank C. Meinecke Germany

Okito Yamashita Japan

Paroma Varma

1.2k ×1.3

CN

126 ×0.4

CMN

148 ×1.0

AI

42 ×0.4

NEURO

126 ×1.5

CVPR

Citations per year, relative to Paroma Varma Paroma Varma (= 1×) peers Okito Yamashita

Countries citing papers authored by Paroma Varma

Since Specialization

Citations

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

Fields of papers citing papers by Paroma Varma

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Paroma Varma

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

19 of 19 papers shown

1.

Böehm, Matthias, Paroma Varma, & Doris Xin. (2022). DEEM'22: Data Management for End-to-End Machine Learning. Proceedings of the 2022 International Conference on Management of Data. 2548–2549.

2.

Varma, Paroma, et al.. (2022). Load Balancing Optimization Based on Enhanced Genetic Algorithm in Cloud Computing. International Journal for Research in Applied Science and Engineering Technology. 10(6). 2071–2075. 1 indexed citations

3.

Varma, Paroma, et al.. (2021). Machine Learning Based Breast Cancer Visualization and Classification. 1–6. 1 indexed citations

4.

Córdova‐Palomera, Aldo, Catherine Tcheandjieu, Jason Fries, et al.. (2020). Cardiac Imaging of Aortic Valve Area From 34 287 UK Biobank Participants Reveals Novel Genetic Associations and Shared Genetic Comorbidity With Multiple Disease Phenotypes. Circulation Genomic and Precision Medicine. 13(6). e003014–e003014. 10 indexed citations

5.

Donoghue, Thomas, Erik Peterson, Paroma Varma, et al.. (2020). Parameterizing neural power spectra into periodic and aperiodic components. Nature Neuroscience. 23(12). 1655–1665. 1047 indexed citations breakdown →

6.

Fries, Jason, Paroma Varma, Ke Xiao, et al.. (2019). Weakly supervised classification of aortic valve malformations using unlabeled cardiac MRI sequences. Nature Communications. 10(1). 3111–3111. 56 indexed citations

7.

Varma, Paroma, Frédéric Sala, Shiori Sagawa, et al.. (2019). Multi-Resolution Weak Supervision for Sequential Data. Neural Information Processing Systems. 32. 192–203. 2 indexed citations

8.

Varma, Paroma, et al.. (2019). Learning Dependency Structures for Weak Supervision Models. International Conference on Machine Learning. 6418–6427. 6 indexed citations

9.

Krishna, Ranjay, et al.. (2019). Scene Graph Prediction With Limited Labels. PubMed. 2019. 2580–2590. 16 indexed citations

10.

Varma, Paroma, et al.. (2019). Scene Graph Prediction with Limited Labels. 36 indexed citations

11.

Varma, Paroma, et al.. (2019). Utilizing Weak Supervision to Infer Complex Objects and Situations in Autonomous Driving Data. 119–125. 1 indexed citations

12.

Varma, Paroma & Christopher Ré. (2018). Snuba. Proceedings of the VLDB Endowment. 12(3). 223–236. 66 indexed citations

13.

Zhang, Jian, Max W. Y. Lam, Stephanie Wang, et al.. (2018). Exploring the Utility of Developer Exhaust. PubMed. 2018. 1–7. 1 indexed citations

14.

Varma, Paroma, Dan Iter, Christopher De, & Christopher Ré. (2017). Flipper. 1–5. 11 indexed citations

15.

Varma, Paroma, Bryan He, Payal Bajaj, et al.. (2017). Inferring Generative Model Structure with Static Analysis.. PubMed. 30. 239–249. 6 indexed citations

16.

Varma, Paroma, Bryan He, Dan Iter, et al.. (2016). Socratic Learning: Correcting Misspecified Generative Models using Discriminative Models. arXiv (Cornell University). 3 indexed citations

17.

Zhong, Jingshan, Lei Tian, Paroma Varma, & Laura Waller. (2016). Nonlinear Optimization Algorithm for Partially Coherent Phase Retrieval and Source Recovery. IEEE Transactions on Computational Imaging. 2(3). 310–322. 31 indexed citations

18.

Varma, Paroma & Gordon Wetzstein. (2016). Efficient 3D Deconvolution Microscopy with Proximal Algorithms. JT3A.44–JT3A.44.

19.

Phillips, Zachary F., et al.. (2015). Design of a Domed LED Illuminator for High-Angle Computational Illumination. ITh1A.2–ITh1A.2. 1 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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