Samuel J. Gershman
- General Decision Sciences top 0.2%
- Decision-Making and Behavioral Economics 28
- Cognitive Neuroscience top 0.1%
- Neural dynamics and brain function 72
- Neural and Behavioral Psychology Studies 52
- Memory and Neural Mechanisms 41
- Functional Brain Connectivity Studies 13
- Applied Psychology top 1%
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- Child and Animal Learning Development 19
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- Reinforcement Learning in Robotics 15
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- Neuroscience and Neuropharmacology Research 15
- Co-authors
- Nathaniel D. DawYael NivMatthew BotvinickDavid M. BleiPeter DayanJoshua B. TenenbaumBen SeymourRaymond J. Dolan
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Samuel J. Gershman
201 papers receiving 9.9k citations
Hit Papers
Peers
Comparison fields: 5 of 190
- General Decision Sciences 1.0k
- Cognitive Neuroscience 6.6k
- Experimental and Cognitive Psychology 1.4k
- Applied Psychology 516
- Developmental and Educational Psychology 1.1k
Countries citing papers authored by Samuel J. Gershman
This map shows the geographic impact of Samuel J. Gershman'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 Samuel J. Gershman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samuel J. Gershman more than expected).
Fields of papers citing papers by Samuel J. Gershman
This network shows the impact of papers produced by Samuel J. Gershman. 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 Samuel J. Gershman. The network helps show where Samuel J. Gershman may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Samuel J. Gershman, 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 | 2025 | 0 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 4 | |
| 5 | 2023 | 9 | |
| 6 | 2023 | 10 | |
| 7 | 2023 | 10 | |
| 8 | 2022 | 3 | |
| 9 | 2021 | 14 | |
| 10 | 2021 | 37 | |
| 11 | 2020 | 15 | |
| 12 | 2020 | 2 | |
| 13 | 2020 | 48 | |
| 14 | 2019 | 18 | |
| 15 | 2018 | 34 | |
| 16 | Explaining Human Decision Making in Optimal Stopping Tasks. | 2018 | 1 |
| 17 | 2017 | 31 | |
| 18 | Multitasking versus multiplexing: Toward a normative account of limitations in the simultaneous execution of control-demanding behaviors | 2014 | 1 |
| 19 | Amortized Inference in Probabilistic Reasoning | 2014 | 81 |
| 20 | Perceptual Multistability as Markov Chain Monte Carlo Inference | 2009 | 15 |
About Samuel J. Gershman
Samuel J. Gershman is a scholar working on General Decision Sciences, Cognitive Neuroscience and Artificial Intelligence, having authored 210 papers that have together received 10.1k indexed citations. Recurring topics across this work include Neural dynamics and brain function (72 papers), Neural and Behavioral Psychology Studies (52 papers), Memory and Neural Mechanisms (41 papers), Decision-Making and Behavioral Economics (28 papers), Child and Animal Learning Development (19 papers), Reinforcement Learning in Robotics (15 papers), Neuroscience and Neuropharmacology Research (15 papers) and Functional Brain Connectivity Studies (13 papers). The work is most often cited by research in General Decision Sciences (1.0k citations), Cognitive Neuroscience (6.6k citations) and Experimental and Cognitive Psychology (1.4k citations). Samuel J. Gershman has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Nathaniel D. Daw, Yael Niv, Matthew Botvinick, David M. Blei, Peter Dayan, Joshua B. Tenenbaum, Ben Seymour, Raymond J. Dolan, Kimberly Stachenfeld and Naoshige Uchida. Their work appears in journals such as Science, Cell 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.