D. A. Podoprikhin

9 papers receiving 378 citations

Hit Papers

Averaging Weights Leads to Wider Optima and Better Genera...20182026202020232018100200300

Peers

D. A. Podoprikhin
Comparison fields: 5 of 87
  • Artificial Intelligence 242
  • Computer Vision and Pattern Recognition 176
  • Computational Theory and Mathematics 31
  • Geometry and Topology 30
  • Radiology, Nuclear Medicine and Imaging 23
Replace Thomas Elsken with:
Thomas Elsken Germany
Jaz Kandola United Kingdom
Kai-Min Chung United States
Basarab Mateï France
Takashi Takenouchi Japan
Guangliang Chen United States
Predrag Neskovic United States
Jacob Yadegar United States
Dan Kushnir United States
Piero Zamperoni Germany
D. A. Podoprikhin relative to Thomas Elsken Germany Thomas Elsken's profile →
Citations per field
00.5×10×17×
Thomas Elsken · 1×
Citations per year

Countries citing papers authored by D. A. Podoprikhin

Since Specialization
Citations

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

Fields of papers citing papers by D. A. Podoprikhin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D. A. Podoprikhin. 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 D. A. Podoprikhin. The network helps show where D. A. Podoprikhin may publish in the future.

Co-authorship network of co-authors of D. A. Podoprikhin

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

All Works

11 of 11 papers shown
#WorkIndexed citations
1 1
2 0
3
Averaging Weights Leads to Wider Optima and Better Generalizationbreakdown →
329
4 0
5
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs
38
6 4
7 12
8 5
9 10
10 11
11 1

About D. A. Podoprikhin

D. A. Podoprikhin is a scholar working on Geometry and Topology, Applied Mathematics and Computational Theory and Mathematics, having authored 11 papers that have together received 411 indexed citations. Recurring topics across this work include Optimization and Variational Analysis (6 papers), Fixed Point Theorems Analysis (6 papers) and Functional Equations Stability Results (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (176 citations), Artificial Intelligence (242 citations) and Computational Mathematics (3 citations). D. A. Podoprikhin has collaborated with scholars based in Russia, United States and Tajikistan. Frequent co-authors include Timur Garipov, Andrew Gordon Wilson, Pavel Izmailov, Dmitry Vetrov and Т. Н. Фоменко. Their work appears in journals such as Journal of Optimization Theory and Applications, Topology and its Applications and Journal of Fixed Point Theory and Applications.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026