Deep Ray

1.3k citations
27 papers · 820 · h-index 13

Impact in

    • Model Reduction and Neural Networks
    • Fluid Dynamics and Turbulent Flows
    • Computational Fluid Dynamics and Aerodynamics
    • Advanced Numerical Methods in Computational Mathematics
    • Fluid Dynamics and Vibration Analysis

Papers in

Deep Ray

26 papers receiving 794 citations

Peers

Deep Ray
Comparison fields: 5 of 81
  • Statistical and Nonlinear Physics 499
  • Computational Mechanics 402
  • Statistics, Probability and Uncertainty 130
  • Numerical Analysis 49
  • Computational Mathematics 3
Replace Jens Berg with:
Jens Berg Sweden
Masayuki Yano United States
Eurika Kaiser United States
Lionel Mathelin France
Todd Oliver United States
M. Damodaran Singapore
Matthew J. Zahr United States
Roberto Molinaro Switzerland
Jonathan H. Tu United States
Alessandro Alla Italy
Deep Ray relative to Jens Berg Sweden Jens Berg's profile →
Citations per field
00.5×
Jens Berg · 1×
Citations per year

Countries citing papers authored by Deep Ray

Since Specialization
Citations

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

Fields of papers citing papers by Deep Ray

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Deep Ray, 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 Deep Ray Line = papers co-authored together Deep Ray links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019199
2 2020105
3 2018101
4 202054
5 202050
6 201949
7 202045
8 201637
9 202234
10 202423
11 202120
12 202315
13 202314
14 202112
15 202311
16 202210
17 20248
18 20247
19 20177
20 20234

About Deep Ray

Deep Ray is a scholar working on Statistical and Nonlinear Physics, Computational Mechanics, Computer Vision and Pattern Recognition, Artificial Intelligence and Statistics, Probability and Uncertainty, having authored 27 papers that have together received 820 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (16 papers), Fluid Dynamics and Turbulent Flows (8 papers), Generative Adversarial Networks and Image Synthesis (7 papers), Computational Fluid Dynamics and Aerodynamics (7 papers), Probabilistic and Robust Engineering Design (5 papers), Gaussian Processes and Bayesian Inference (4 papers), Advanced Numerical Methods in Computational Mathematics (3 papers) and Medical Image Segmentation Techniques (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (499 citations), Computational Mechanics (402 citations), Statistics, Probability and Uncertainty (130 citations), Numerical Analysis (49 citations) and Computational Mathematics (3 citations). Deep Ray has collaborated with scholars based in United States, Switzerland and India. Frequent co-authors include Jan S. Hesthaven, Qian Wang, Siddhartha Mishra, Assad A. Oberai, Praveen Chandrashekar, Dhruv Patel, Christian Rohde, Ulrik Skre Fjordholm, E. A. Johnson and Thomas J.R. Hughes. Their work appears in journals such as Journal of Computational Physics, Computer Methods in Applied Mechanics and Engineering, Communications in Computational Physics, Engineering With Computers and SIAM Journal on Scientific Computing.

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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