Randall Balestriero

915 citations
26 papers · 218 indexed · h-index 6

Randall Balestriero

24 papers receiving 209 citations

Peers

Randall Balestriero
Comparison fields: 5 of 54
  • Geophysics 115
  • Computational Mathematics 3
  • Developmental Biology 8
  • Artificial Intelligence 116
  • Signal Processing 16
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Yuansheng Zhang China
Yunfeng Chen China
Ge Li China
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Ciriaco D’Ambrosio Italy
Teimuraz Matcharashvili Georgia
Wail A. Mousa Saudi Arabia
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Joydeep Bhattacharyya United States
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Citations per field
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Citations per year

Countries citing papers authored by Randall Balestriero

Since Specialization
Citations

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

Fields of papers citing papers by Randall Balestriero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Randall Balestriero, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Randall Balestriero Line = papers co-authored together Randall Balestriero links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202410
2 20235
3 20232
4 20232
5 20222
6 202214
7 20224
8 202121
9 20217
10
Analytical Probability Distributions and Exact Expectation-Maximization for Deep Generative Networks
20201
11 2020121
12 20201
13
A Hessian Based Complexity Measure for Deep Networks.
20191
14 20191
15
A Max-Affine Spline Perspective of Recurrent Neural Networks
20191
16
A spline theory of deep networks
20188
17
Fast Chirplet Transform Injects Priors in Deep Learning of Animal Calls and Speech
20175
18
Fast Chirplet Transform feeding CNN, application to orca and bird bioacoustics.
20160
19 20161
20 20153

About Randall Balestriero

Randall Balestriero is a scholar working on Computational Mathematics, Signal Processing, Computer Vision and Pattern Recognition, Artificial Intelligence and Oceanography, having authored 26 papers that have together received 218 indexed citations. Recurring topics across this work include Underwater Acoustics Research (6 papers), Anomaly Detection Techniques and Applications (5 papers), Image and Signal Denoising Methods (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), Sparse and Compressive Sensing Techniques (3 papers), Marine animal studies overview (3 papers), Speech and Audio Processing (3 papers) and Generative Adversarial Networks and Image Synthesis (3 papers). The work is most often cited by research in Geophysics (115 citations), Computational Mathematics (3 citations), Developmental Biology (8 citations), Artificial Intelligence (116 citations) and Signal Processing (16 citations). Randall Balestriero has collaborated with scholars based in United States, France and United Kingdom. Frequent co-authors include Richard G. Baraniuk, Maarten V. de Hoop, Léonard Seydoux, Piero Poli, Michel Campillo, Ashok Veeraraghavan, Vishwanath Saragadam, Yann LeCun, Hervé Glotin and Hervé Glotin. Their work appears in journals such as The Journal of the Acoustical Society of America, IEEE Signal Processing Letters, Bulletin of the Seismological Society of America, Nature Communications and IEEE Transactions on Geoscience and Remote Sensing.

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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