Anima Anandkumar
Impact in
- Computational Mathematics top 0.5%
- Tensor decomposition and applications
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- Advanced Neural Network Applications
- Multimodal Machine Learning Applications
Papers in
-
- Domain Adaptation and Few-Shot Learning 11
- Stochastic Gradient Optimization Techniques 9
- Machine Learning and Algorithms 9
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- Advanced Neural Network Applications 19
- Multimodal Machine Learning Applications 8
- Co-authors
- Kamyar Azizzadenesheli (21 shared papers)Zongyi Li (12 shared papers)Zhiding Yu (21 shared papers)Jean Kossaifi (16 shared papers)Gege Wen (2 shared papers)Sally M. Benson (2 shared papers)Nikola Kovachki (5 shared papers)Yannis Panagakis (5 shared papers)
- Journals
- Nature Machine Intelligence (3 papers)Journal of Machine Learning Research (2 papers)Journal of Endourology (2 papers)Quantum (2 papers)Proceedings of the National Academy of Sciences (2 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Anima Anandkumar
117 papers receiving 3.7k citations
Anima Anandkumar's Hit Papers
Peers
Comparison fields: 5 of 159
- Computational Mathematics 241
- Computer Vision and Pattern Recognition 913
- Statistical and Nonlinear Physics 502
- Artificial Intelligence 1.1k
- Environmental Engineering 299
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-authors
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
Showing the 20 most-cited of 127 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Physics-informed machine learning: case studies for weather and climate modelling Hit paper breakdown → | 2021 | 384 |
| 2 | U-FNO—An enhanced Fourier neural operator-based deep-learning model for multiphase flow Hit paper breakdown → | 2022 | 314 |
| 3 | Neural-Fly enables rapid learning for agile flight in strong winds Hit paper breakdown → | 2022 | 169 |
| 4 | 2016 | 135 | |
| 5 | Fourier Neural Operator for Parametric Partial Differential Equations | 2021 | 132 |
| 6 | VoxFormer: Sparse Voxel Transformer for Camera-Based 3D Semantic Scene Completion Hit paper breakdown → | 2023 | 130 |
| 7 | Physics-Informed Neural Operator for Learning Partial Differential Equations Hit paper breakdown → | 2024 | 122 |
| 8 | Neural operators for accelerating scientific simulations and design Hit paper breakdown → | 2024 | 118 |
| 9 | Born Again Neural Networks | 2018 | 115 |
| 10 | FourCastNet: Accelerating Global High-Resolution Weather Forecasting Using Adaptive Fourier Neural Operators Hit paper breakdown → | 2023 | 113 |
| 11 | 2022 | 107 | |
| 12 | 2018 | 101 | |
| 13 | Shaping the Water-Harvesting Behavior of Metal–Organic Frameworks Aided by Fine-Tuned GPT Models Hit paper breakdown → | 2023 | 95 |
| 14 | Real-time high-resolution CO2 geological storage prediction using nested Fourier neural operators Hit paper breakdown → | 2023 | 93 |
| 15 | 2023 | 89 | |
| 16 | 2021 | 89 | |
| 17 | State-specific protein–ligand complex structure prediction with a multiscale deep generative model Hit paper breakdown → | 2024 | 79 |
| 18 | 2014 | 79 | |
| 19 | 2020 | 76 | |
| 20 | 2022 | 73 |
About Anima Anandkumar
Anima Anandkumar is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mathematics, Statistical and Nonlinear Physics and Computational Mechanics, having authored 127 papers that have together received 3.8k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (19 papers), Tensor decomposition and applications (18 papers), Model Reduction and Neural Networks (14 papers), Domain Adaptation and Few-Shot Learning (11 papers), Stochastic Gradient Optimization Techniques (9 papers), Machine Learning and Algorithms (9 papers), Surgical Simulation and Training (8 papers) and Multimodal Machine Learning Applications (8 papers). The work is most often cited by research in Computational Mathematics (241 citations), Computer Vision and Pattern Recognition (913 citations), Statistical and Nonlinear Physics (502 citations), Artificial Intelligence (1.1k citations) and Environmental Engineering (299 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, Gege Wen, Sally M. Benson, Nikola Kovachki, Yannis Panagakis, Jose M. Álvarez and Chaowei Xiao. Their work appears in journals such as Nature Machine Intelligence, Journal of Machine Learning Research, Journal of Endourology, Quantum and Proceedings of the National Academy of Sciences.
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.