Anima Anandkumar
- Computational Mathematics top 0.5%
- Tensor decomposition and applications 16
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- Advanced Neural Network Applications 19
- Advanced Vision and Imaging 8
- Multimodal Machine Learning Applications 8
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- Model Reduction and Neural Networks 11
- Artificial Intelligence top 1%
- Domain Adaptation and Few-Shot Learning 11
- Stochastic Gradient Optimization Techniques 9
- Machine Learning and Algorithms 8
- Health Informatics top 5%
Anima Anandkumar
109 papers receiving 2.8k citations
Hit Papers
Peers
Comparison fields: 5 of 155
- Computational Mathematics 206
- Computer Vision and Pattern Recognition 783
- Statistical and Nonlinear Physics 365
- Artificial Intelligence 926
- Health Informatics 28
Countries citing papers authored by Anima Anandkumar
This map shows the geographic impact of Anima Anandkumar'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 Anima Anandkumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anima Anandkumar more than expected).
Fields of papers citing papers by Anima Anandkumar
This network shows the impact of papers produced by Anima Anandkumar. 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 Anima Anandkumar. The network helps show where Anima Anandkumar may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Anima Anandkumar, 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 | 2025 | 12 | |
| 2 | 2024 | 12 | |
| 3 | 2024 | 20 | |
| 4 | 2023 | 11 | |
| 5 | FourCastNet: Accelerating Global High-Resolution Weather Forecasting Using Adaptive Fourier Neural Operatorsbreakdown → | 2023 | 98 |
| 6 | 2023 | 3 | |
| 7 | Shaping the Water-Harvesting Behavior of Metal–Organic Frameworks Aided by Fine-Tuned GPT Modelsbreakdown → | 2023 | 79 |
| 8 | Adversarially Robust 3D Point Cloud Recognition Using Self-Supervisions | 2021 | 16 |
| 9 | 2021 | 77 | |
| 10 | Coach-Player Multi-agent Reinforcement Learning for Dynamic Team Composition | 2021 | 4 |
| 11 | Neural Networks with Recurrent Generative Feedback | 2020 | 3 |
| 12 | Multipole Graph Neural Operator for Parametric Partial Differential Equations | 2020 | 8 |
| 13 | Convolutional Tensor-Train LSTM for Spatio-temporal Learning | 2020 | 5 |
| 14 | Regret Bound of Adaptive Control in Linear Quadratic Gaussian (LQG) Systems | 2020 | 3 |
| 15 | Stochastically Rank-Regularized Tensor Regression Networks. | 2019 | 2 |
| 16 | Competitive Gradient Descent | 2019 | 5 |
| 17 | Born Again Neural Networks | 2018 | 109 |
| 18 | Active Learning with Partial Feedback | 2018 | 6 |
| 19 | signSGD with Majority Vote is Communication Efficient And Byzantine Fault Tolerant | 2018 | 7 |
| 20 | Generalization Bounds for Neural Networks through Tensor Factorization. | 2015 | 6 |
About Anima Anandkumar
Anima Anandkumar is a scholar working on Computational Mathematics, Health Informatics, Computer Vision and Pattern Recognition, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 118 papers that have together received 2.9k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (19 papers), Tensor decomposition and applications (16 papers), Domain Adaptation and Few-Shot Learning (11 papers), Model Reduction and Neural Networks (11 papers), Stochastic Gradient Optimization Techniques (9 papers), Machine Learning and Algorithms (8 papers), Advanced Vision and Imaging (8 papers) and Multimodal Machine Learning Applications (8 papers). The work is most often cited by research in Computational Mathematics (206 citations), Computer Vision and Pattern Recognition (783 citations), Statistical and Nonlinear Physics (365 citations), Artificial Intelligence (926 citations) and Health Informatics (28 citations). Anima Anandkumar has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Kamyar Azizzadenesheli, Zongyi Li, Zhiding Yu, Jean Kossaifi, Sally M. Benson, Gege Wen, Nikola Kovachki, Yannis Panagakis, Burigede Liu and José M. Alvarez. Their work appears in journals such as Nature Machine Intelligence, Journal of Endourology, Quantum, Proceedings of the National Academy of Sciences and Journal of Machine Learning Research.
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.