Lazar Valkov

619 total citations
3 papers, 107 citations indexed

About

Lazar Valkov is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics. According to data from OpenAlex, Lazar Valkov has authored 3 papers receiving a total of 107 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 1 paper in Computer Vision and Pattern Recognition and 1 paper in Statistical and Nonlinear Physics. Recurrent topics in Lazar Valkov's work include Ferroelectric and Negative Capacitance Devices (1 paper), Parallel Computing and Optimization Techniques (1 paper) and Domain Adaptation and Few-Shot Learning (1 paper). Lazar Valkov is often cited by papers focused on Ferroelectric and Negative Capacitance Devices (1 paper), Parallel Computing and Optimization Techniques (1 paper) and Domain Adaptation and Few-Shot Learning (1 paper). Lazar Valkov collaborates with scholars based in United States, United Kingdom and India. Lazar Valkov's co-authors include Charles Sutton, Akash Srivastava, Chris Russell, Michael U. Gutmann, James Smith, Zsolt Kira, Swarat Chaudhuri, Leonid Karlinsky and Rogério Feris and has published in prestigious journals such as Edinburgh Research Explorer (University of Edinburgh) and arXiv (Cornell University).

In The Last Decade

Lazar Valkov

3 papers receiving 98 citations

Peers

Countries citing papers authored by Lazar Valkov

Since Specialization

Citations

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

Fields of papers citing papers by Lazar Valkov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lazar Valkov

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

All Works

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3 of 3 papers shown

#	Work	Indexed citations
1	Adaptive Memory Replay for Continual Learning 2024 ·James Smith, Lazar Valkov, (unknown), (unknown), Rogério Feris, Zsolt Kira, Leonid Karlinsky	4
2	HOUDINI: Lifelong Learning as Program Synthesis 2018 ·arXiv (Cornell University) ·Lazar Valkov, (unknown), Akash Srivastava, Charles Sutton, Swarat Chaudhuri	7
3	VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning 2017 ·Edinburgh Research Explorer (University of Edinburgh) ·Akash Srivastava, Lazar Valkov, Chris Russell, Michael U. Gutmann, Charles Sutton	96

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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