Manzil Zaheer
- Artificial Intelligence top 5%
- Topic Modeling 12
- Natural Language Processing Techniques 9
- Data Stream Mining Techniques 3
- Stochastic Gradient Optimization Techniques 3
- Advanced Graph Neural Networks 3
- Domain Adaptation and Few-Shot Learning 3
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- Multimodal Machine Learning Applications 4
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- Advanced Bandit Algorithms Research 3
- Co-authors
- Anit Kumar SahuAmeet TalwalkarTian LiMaziar SanjabiVirginia SmithAndrew McCallumRajarshi DasAmr Ahmed
- Cited by
- Artificial IntelligenceComputer Science ApplicationsComputer Vision and Pattern Recognition
- Journals
- Transactions of the Association for Computational Linguistics (1 paper)ArXiv.org (1 paper)Repository for Publications and Research Data (ETH Zurich) (1 paper)
- Partner nations
- United StatesSwitzerlandCanada
In The Last Decade
Manzil Zaheer
22 papers receiving 388 citations
Peers
Comparison fields: 5 of 54
- Artificial Intelligence 340
- Computer Science Applications 22
- Computer Vision and Pattern Recognition 82
- Health Informatics 3
- Information Systems 42
Countries citing papers authored by Manzil Zaheer
This map shows the geographic impact of Manzil Zaheer'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 Manzil Zaheer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manzil Zaheer more than expected).
Fields of papers citing papers by Manzil Zaheer
This network shows the impact of papers produced by Manzil Zaheer. 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 Manzil Zaheer. The network helps show where Manzil Zaheer may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Manzil Zaheer, 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 | 2024 | 5 | |
| 2 | 2023 | 14 | |
| 3 | 2023 | 22 | |
| 4 | 2023 | 0 | |
| 5 | 2023 | 1 | |
| 6 | 2022 | 1 | |
| 7 | Latent Programmer: Discrete Latent Codes for Program Synthesis | 2021 | 1 |
| 8 | Sketch based Memory for Neural Networks | 2021 | 1 |
| 9 | 2021 | 71 | |
| 10 | 2021 | 17 | |
| 11 | Differentiable Meta-Learning in Contextual Bandits. | 2020 | 1 |
| 12 | PLLay: Efficient Topological Layer based on Persistent Landscapes | 2020 | 5 |
| 13 | Differentiable Meta-Learning of Bandit Policies. | 2020 | 4 |
| 14 | 2020 | 17 | |
| 15 | 2019 | 17 | |
| 16 | 2019 | 1 | |
| 17 | 2019 | 32 | |
| 18 | Point Cloud GAN | 2018 | 7 |
| 19 | On the Convergence of Federated Optimization in Heterogeneous Networks. | 2018 | 135 |
| 20 | 2018 | 8 |
About Manzil Zaheer
Manzil Zaheer is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Software, having authored 23 papers that have together received 397 indexed citations. Recurring topics across this work include Topic Modeling (12 papers), Natural Language Processing Techniques (9 papers), Multimodal Machine Learning Applications (4 papers), Data Stream Mining Techniques (3 papers), Stochastic Gradient Optimization Techniques (3 papers), Advanced Graph Neural Networks (3 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Advanced Bandit Algorithms Research (3 papers). The work is most often cited by research in Artificial Intelligence (340 citations), Computer Science Applications (22 citations) and Computer Vision and Pattern Recognition (82 citations). Manzil Zaheer has collaborated with scholars based in United States, Switzerland and Canada. Frequent co-authors include Anit Kumar Sahu, Ameet Talwalkar, Tian Li, Maziar Sanjabi, Virginia Smith, Andrew McCallum, Rajarshi Das, Amr Ahmed, Lazaros Polymenakos and Ethan Perez. Their work appears in journals such as Transactions of the Association for Computational Linguistics, ArXiv.org and Repository for Publications and Research Data (ETH Zurich).
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.