Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
U-FNO—An enhanced Fourier neural operator-based deep-learning model for multiphase flow
2022273 citationsZongyi Li, Kamyar Azizzadenesheli et al.profile →
Neural-Fly enables rapid learning for agile flight in strong winds
2022148 citationsKamyar Azizzadenesheli, Anima Anandkumar et al.profile →
VoxFormer: Sparse Voxel Transformer for Camera-Based 3D Semantic Scene Completion
2023111 citationsZhiding Yu, Christopher Choy et al.profile →
Physics-Informed Neural Operator for Learning Partial Differential Equations
2024103 citationsZongyi Li, Nikola Kovachki et al.profile →
FourCastNet: Accelerating Global High-Resolution Weather Forecasting Using Adaptive Fourier Neural Operators
202398 citationsThorsten Kurth, Shashank Subramanian et al.profile →
Neural operators for accelerating scientific simulations and design
202490 citationsKamyar Azizzadenesheli, Nikola Kovachki et al.profile →
Real-time high-resolution CO2 geological storage prediction using nested Fourier neural operators
202379 citationsZongyi Li, Kamyar Azizzadenesheli et al.profile →
Shaping the Water-Harvesting Behavior of Metal–Organic Frameworks Aided by Fine-Tuned GPT Models
202379 citationsZhiling Zheng, Ali H. Alawadhi et al.Journal of the American Chemical Societyprofile →
State-specific protein–ligand complex structure prediction with a multiscale deep generative model
Countries citing papers authored by Anima Anandkumar
Since
Specialization
Citations
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 of co-authors of Anima Anandkumar
This figure shows the co-authorship network connecting the top 25 collaborators of Anima Anandkumar.
A scholar is included among the top collaborators of Anima Anandkumar 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 Anima Anandkumar. Anima Anandkumar is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zheng, Zhiling, Ali H. Alawadhi, Saumil Chheda, et al.. (2023). Shaping the Water-Harvesting Behavior of Metal–Organic Frameworks Aided by Fine-Tuned GPT Models. Journal of the American Chemical Society. 145(51). 28284–28295.79 indexed citations breakdown →
8.
Sun, Jiachen, Yulong Cao, Christopher Choy, et al.. (2021). Adversarially Robust 3D Point Cloud Recognition Using Self-Supervisions. CaltechAUTHORS (California Institute of Technology). 34.16 indexed citations
Liu, Bo, Qiang Liu, Peter Stone, et al.. (2021). Coach-Player Multi-agent Reinforcement Learning for Dynamic Team Composition. CaltechAUTHORS (California Institute of Technology). 6860–6870.4 indexed citations
11.
Huang, Yujia, et al.. (2020). Neural Networks with Recurrent Generative Feedback. CaltechAUTHORS (California Institute of Technology). 33. 535–545.3 indexed citations
12.
Li, Zongyi, Nikola Kovachki, Kamyar Azizzadenesheli, et al.. (2020). Multipole Graph Neural Operator for Parametric Partial Differential Equations. CaltechAUTHORS (California Institute of Technology). 33. 6755–6766.8 indexed citations
13.
Su, Jiahao, Wonmin Byeon, Jean Kossaifi, et al.. (2020). Convolutional Tensor-Train LSTM for Spatio-temporal Learning. CaltechAUTHORS (California Institute of Technology). 33. 13714–13726.5 indexed citations
14.
Azizzadenesheli, Kamyar, et al.. (2020). Regret Bound of Adaptive Control in Linear Quadratic Gaussian (LQG) Systems. King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology).3 indexed citations
15.
Kossaifi, Jean, et al.. (2019). Stochastically Rank-Regularized Tensor Regression Networks.. CaltechAUTHORS (California Institute of Technology).2 indexed citations
Furlanello, Tommaso, Zachary C. Lipton, Michael Tschannen, Laurent Itti, & Anima Anandkumar. (2018). Born Again Neural Networks. CaltechAUTHORS (California Institute of Technology). 1607–1616.109 indexed citations
18.
Hu, Peiyun, Zachary C. Lipton, Anima Anandkumar, & Deva Ramanan. (2018). Active Learning with Partial Feedback. CaltechAUTHORS (California Institute of Technology).6 indexed citations
19.
Bernstein, Jeremy, et al.. (2018). signSGD with Majority Vote is Communication Efficient And Byzantine Fault Tolerant. arXiv (Cornell University).7 indexed citations
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.