Vikash Kumar
Impact in
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- Domain Adaptation and Few-Shot Learning
- Reinforcement Learning in Robotics
- Machine Learning and ELM
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- Physical Unclonable Functions (PUFs) and Hardware Security
Papers in
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- Reinforcement Learning in Robotics 5
- Domain Adaptation and Few-Shot Learning 4
- Adversarial Robustness in Machine Learning 2
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- Multimodal Machine Learning Applications 4
- Co-authors
- Rohit Lal (3 shared papers)Somanath Tripathy (2 shared papers)Jimson Mathew (2 shared papers)Igor Mordatch (2 shared papers)Aravind Rajeswaran (2 shared papers)Ofir Nachum (1 shared paper)Michael J. Ahn (1 shared paper)Anirban Chakraborty (2 shared papers)
- Journals
- International Journal of Computer Vision (1 paper)Computers & Geosciences (1 paper)IET Circuits Devices & Systems (1 paper)Smart innovation, systems and technologies (2 papers)International Conference on Learning Representations (1 paper)
- Partner nations
- IndiaUnited States
In The Last Decade
Vikash Kumar
13 papers receiving 81 citations
Peers
Comparison fields: 5 of 45
- Artificial Intelligence 50
- Hardware and Architecture 10
- Computer Vision and Pattern Recognition 27
- Control and Systems Engineering 10
- Geophysics 5
Countries citing papers authored by Vikash Kumar
This map shows the geographic impact of Vikash Kumar'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 Vikash Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vikash Kumar more than expected).
Fields of papers citing papers by Vikash Kumar
This network shows the impact of papers produced by Vikash Kumar. 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 Vikash Kumar. The network helps show where Vikash Kumar may publish in the future.
Co-authors
The 19 scholars most cited alongside Vikash Kumar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 21 | |
| 2 | 2021 | 9 | |
| 3 | Multi-Agent Manipulation via Locomotion using Hierarchical Sim2Real | 2019 | 8 |
| 4 | 2021 | 7 | |
| 5 | A Game Theoretic Framework for Model Based Reinforcement Learning | 2020 | 6 |
| 6 | 2018 | 6 | |
| 7 | 2023 | 6 | |
| 8 | Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines | 2018 | 5 |
| 9 | 1989 | 5 | |
| 10 | 2021 | 4 | |
| 11 | Dynamics-Aware Unsupervised Skill Discovery | 2020 | 3 |
| 12 | 2021 | 3 | |
| 13 | 2020 | 2 | |
| 14 | 2025 | 0 | |
| 15 | 2021 | 0 | |
| 16 | 2019 | 0 | |
| 17 | 2019 | 0 |
About Vikash Kumar
Vikash Kumar is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Sociology and Political Science and Hardware and Architecture, having authored 17 papers that have together received 85 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (5 papers), Multimodal Machine Learning Applications (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), Adversarial Robustness in Machine Learning (2 papers), Advanced Memory and Neural Computing (2 papers), Integrated Circuits and Semiconductor Failure Analysis (2 papers), Physical Unclonable Functions (PUFs) and Hardware Security (2 papers) and Cancer-related molecular mechanisms research (2 papers). The work is most often cited by research in Artificial Intelligence (50 citations), Hardware and Architecture (10 citations), Computer Vision and Pattern Recognition (27 citations), Control and Systems Engineering (10 citations) and Geophysics (5 citations). Vikash Kumar has collaborated with scholars based in India and United States. Frequent co-authors include Rohit Lal, Somanath Tripathy, Jimson Mathew, Igor Mordatch, Aravind Rajeswaran, Ofir Nachum, Michael J. Ahn, Anirban Chakraborty, Shixiang Gu and Sergey Levine. Their work appears in journals such as International Journal of Computer Vision, Computers & Geosciences, IET Circuits Devices & Systems, Smart innovation, systems and technologies and International Conference on Learning Representations.
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.