Ardavan Saeedi
Impact in
- Artificial Intelligence top 5%
- Reinforcement Learning in Robotics
- Machine Learning and Data Classification
- Topic Modeling
Papers in
-
- Bayesian Methods and Mixture Models 3
- Anomaly Detection Techniques and Applications 2
- Machine Learning and Data Classification 2
- Machine Learning and Algorithms 2
- Topic Modeling 2
- Co-authors
- Karthik Narasimhan (3 shared papers)Joshua B. Tenenbaum (1 shared paper)Tejas D. Kulkarni (1 shared paper)Gholamreza Safaee Ardekani (1 shared paper)Lawrence Tan (1 shared paper)Gang Li (1 shared paper)Seyed Mehdi Jafarnejad (1 shared paper)Daniel C. Alexander (1 shared paper)
- Journals
- PLoS ONE (1 paper)Lecture notes in computer science (1 paper)International Conference on Learning Representations (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)Neural Information Processing Systems (1 paper)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Ardavan Saeedi
9 papers receiving 679 citations
Ardavan Saeedi's Hit Papers
Peers
Comparison fields: 5 of 95
- Artificial Intelligence 376
- Computer Vision and Pattern Recognition 116
- Health Informatics 7
- Oncology 139
- Pathology and Forensic Medicine 67
Countries citing papers authored by Ardavan Saeedi
This map shows the geographic impact of Ardavan Saeedi'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 Ardavan Saeedi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ardavan Saeedi more than expected).
Fields of papers citing papers by Ardavan Saeedi
This network shows the impact of papers produced by Ardavan Saeedi. 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 Ardavan Saeedi. The network helps show where Ardavan Saeedi may publish in the future.
Co-authors
The 25 scholars most cited alongside Ardavan Saeedi, 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 | Hierarchical deep reinforcement learning: integrating temporal abstraction and intrinsic motivation Hit paper breakdown → | 2016 | 318 |
| 2 | 2012 | 181 | |
| 3 | 2019 | 129 | |
| 4 | 2016 | 41 | |
| 5 | Priors over Recurrent Continuous Time Processes | 2011 | 16 |
| 6 | 2015 | 6 | |
| 7 | Discrepancy Ratio: Evaluating Model Performance When Even Experts Disagree on the Truth | 2020 | 3 |
| 8 | Multimodal Prediction and Personalization of Photo Edits with Deep Generative Models | 2018 | 2 |
| 9 | 2022 | 2 | |
| 10 | JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes | 2015 | 1 |
About Ardavan Saeedi
Ardavan Saeedi is a scholar working on Artificial Intelligence, Molecular Biology, Oncology, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 10 papers that have together received 699 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (3 papers), Anomaly Detection Techniques and Applications (2 papers), Machine Learning and Data Classification (2 papers), Machine Learning and Algorithms (2 papers), Topic Modeling (2 papers), Colorectal Cancer Treatments and Studies (1 paper), COVID-19 diagnosis using AI (1 paper) and Cancer Genomics and Diagnostics (1 paper). The work is most often cited by research in Artificial Intelligence (376 citations), Computer Vision and Pattern Recognition (116 citations), Health Informatics (7 citations), Oncology (139 citations) and Pathology and Forensic Medicine (67 citations). Ardavan Saeedi has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Karthik Narasimhan, Joshua B. Tenenbaum, Tejas D. Kulkarni, Gholamreza Safaee Ardekani, Lawrence Tan, Gang Li, Seyed Mehdi Jafarnejad, Daniel C. Alexander, Swami Sankaranarayanan and Nathan Silberman. Their work appears in journals such as PLoS ONE, Lecture notes in computer science, International Conference on Learning Representations, Proceedings of the AAAI Conference on Artificial Intelligence and Neural Information Processing Systems.
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.