Scott Sanner
Impact in
- Artificial Intelligence top 0.5%
- Topic Modeling
- Advanced Graph Neural Networks
- Domain Adaptation and Few-Shot Learning
- AI-based Problem Solving and Planning
- Bayesian Modeling and Causal Inference
- Information Systems top 0.5%
- Recommender Systems and Techniques
Papers in
-
- Bayesian Modeling and Causal Inference 28
- Reinforcement Learning in Robotics 24
- Topic Modeling 23
- Machine Learning and Algorithms 21
- AI-based Problem Solving and Planning 13
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- Recommender Systems and Techniques 30
- Co-authors
- Lexing Xie (12 shared papers)Suvash Sedhain (6 shared papers)Aditya Krishna Menon (4 shared papers)Zheda Mai (8 shared papers)Wray Buntine (2 shared papers)Rishabh Mehrotra (1 shared paper)Hyunwoo Kim (3 shared papers)Ruiwen Li (3 shared papers)
- Journals
- AI Magazine (5 papers)Artificial Intelligence (3 papers)Building and Environment (2 papers)ACM Transactions on the Web (2 papers)Lecture notes in computer science (11 papers)
- Partner nations
- CanadaAustraliaUnited States
In The Last Decade
Scott Sanner
157 papers receiving 4.2k citations
Scott Sanner's Hit Papers
Peers
Comparison fields: 5 of 147
- Artificial Intelligence 2.6k
- Information Systems 1.5k
- Computer Vision and Pattern Recognition 961
- Management Science and Operations Research 368
- Transportation 153
Countries citing papers authored by Scott Sanner
This map shows the geographic impact of Scott Sanner'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 Scott Sanner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Scott Sanner more than expected).
Fields of papers citing papers by Scott Sanner
This network shows the impact of papers produced by Scott Sanner. 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 Scott Sanner. The network helps show where Scott Sanner may publish in the future.
Co-authors
The 25 scholars most cited alongside Scott Sanner, 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 166 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | AutoRec Hit paper breakdown → | 2015 | 846 |
| 2 | Improving LDA topic models for microblogs via tweet pooling and automatic labeling Hit paper breakdown → | 2013 | 367 |
| 3 | Online continual learning in image classification: An empirical survey Hit paper breakdown → | 2021 | 262 |
| 4 | 2018 | 183 | |
| 5 | 2021 | 110 | |
| 6 | 2021 | 108 | |
| 7 | 2019 | 93 | |
| 8 | 2014 | 91 | |
| 9 | 2012 | 83 | |
| 10 | 2019 | 82 | |
| 11 | 2015 | 79 | |
| 12 | 2020 | 79 | |
| 13 | 2023 | 76 | |
| 14 | 2003 | 74 | |
| 15 | 2018 | 73 | |
| 16 | 2017 | 59 | |
| 17 | 2008 | 52 | |
| 18 | 2010 | 51 | |
| 19 | 2012 | 51 | |
| 20 | 2023 | 48 |
About Scott Sanner
Scott Sanner is a scholar working on Artificial Intelligence, Information Systems, Computational Theory and Mathematics, Management Science and Operations Research and Computer Vision and Pattern Recognition, having authored 166 papers that have together received 4.3k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (30 papers), Bayesian Modeling and Causal Inference (28 papers), Reinforcement Learning in Robotics (24 papers), Topic Modeling (23 papers), Formal Methods in Verification (23 papers), Machine Learning and Algorithms (21 papers), AI-based Problem Solving and Planning (13 papers) and Advanced Bandit Algorithms Research (13 papers). The work is most often cited by research in Artificial Intelligence (2.6k citations), Information Systems (1.5k citations), Computer Vision and Pattern Recognition (961 citations), Management Science and Operations Research (368 citations) and Transportation (153 citations). Scott Sanner has collaborated with scholars based in Canada, Australia and United States. Frequent co-authors include Lexing Xie, Suvash Sedhain, Aditya Krishna Menon, Zheda Mai, Wray Buntine, Rishabh Mehrotra, Hyunwoo Kim, Ruiwen Li, Brent Huchuk and William O’Brien. Their work appears in journals such as AI Magazine, Artificial Intelligence, Building and Environment, ACM Transactions on the Web and Lecture notes in computer science.
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.