Daniel Kunin
Impact in
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- Adenosine and Purinergic Signaling
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- Coffee research and impacts
- Cannabis and Cannabinoid Research
Papers in
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- Advanced Thermodynamics and Statistical Mechanics 1
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- Theoretical and Computational Physics 2
- Co-authors
- Zalman Amit (2 shared papers)Brian R. Smith (2 shared papers)Surya Ganguli (3 shared papers)Stéphane Gaskin (1 shared paper)Lei Wu (1 shared paper)Lexing Ying (1 shared paper)Daniel Yamins (2 shared papers)Brian R. Smith (1 shared paper)
- Journals
- Experimental and Clinical Psychopharmacology (2 papers)Alcohol (1 paper)Neural Computation (1 paper)Journal of Statistical Mechanics Theory and Experiment (1 paper)International Conference on Machine Learning (1 paper)
- Partner nations
- United StatesCanadaChina
In The Last Decade
Daniel Kunin
7 papers receiving 24 citations
Peers
Comparison fields: 5 of 20
- Physiology 4
- Pharmacology 11
- Toxicology 2
- Modeling and Simulation 2
- Statistical and Nonlinear Physics 4
Countries citing papers authored by Daniel Kunin
This map shows the geographic impact of Daniel Kunin'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 Daniel Kunin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Kunin more than expected).
Fields of papers citing papers by Daniel Kunin
This network shows the impact of papers produced by Daniel Kunin. 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 Daniel Kunin. The network helps show where Daniel Kunin may publish in the future.
Co-authors
The 13 scholars most cited alongside Daniel Kunin, 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 | 2001 | 7 | |
| 2 | 2001 | 6 | |
| 3 | 2000 | 4 | |
| 4 | Two Routes to Scalable Credit Assignment without Weight Symmetry | 2020 | 2 |
| 5 | 2023 | 2 | |
| 6 | 2022 | 2 | |
| 7 | 2024 | 1 |
About Daniel Kunin
Daniel Kunin is a scholar working on Statistical and Nonlinear Physics, Condensed Matter Physics, Sensory Systems, Nutrition and Dietetics and Computer Networks and Communications, having authored 7 papers that have together received 24 indexed citations. Recurring topics across this work include Theoretical and Computational Physics (2 papers), Biochemical Analysis and Sensing Techniques (2 papers), Olfactory and Sensory Function Studies (2 papers), Advanced Thermodynamics and Statistical Mechanics (1 paper), Nonlinear Dynamics and Pattern Formation (1 paper), Coffee research and impacts (1 paper), Muscle metabolism and nutrition (1 paper) and Markov Chains and Monte Carlo Methods (1 paper). The work is most often cited by research in Physiology (4 citations), Pharmacology (11 citations), Toxicology (2 citations), Modeling and Simulation (2 citations) and Statistical and Nonlinear Physics (4 citations). Daniel Kunin has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Zalman Amit, Brian R. Smith, Surya Ganguli, Stéphane Gaskin, Lei Wu, Lexing Ying, Daniel Yamins, Brian R. Smith, Lauren Gillespie and Jonathan M. Bloom. Their work appears in journals such as Experimental and Clinical Psychopharmacology, Alcohol, Neural Computation, Journal of Statistical Mechanics Theory and Experiment and International Conference on Machine Learning.
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.