Daniel J. Amit
- Cognitive Neuroscience top 0.2%
- Neural dynamics and brain function 51
- Statistical and Nonlinear Physics top 0.2%
- stochastic dynamics and bifurcation 6
- Advanced Thermodynamics and Statistical Mechanics 5
- Condensed Matter Physics top 0.5%
- Theoretical and Computational Physics 15
- Artificial Intelligence top 0.2%
- Neural Networks and Applications 32
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- Neuroscience and Neuropharmacology Research 8
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- Advanced Memory and Neural Computing 32
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- Black Holes and Theoretical Physics 5
- Co-authors
- Haim SompolinskyHanoch GutfreundMisha TsodyksV. Martı́n-MayorStefano FusiLuca PelitiGianluigi MongilloNicolas Brunel
- Journals
- Network Computation in Neural Systems (27 papers)Neural Computation (7 papers)Nuclear Physics B (5 papers)
- Partner nations
- IsraelItalyUnited States
In The Last Decade
Daniel J. Amit
79 papers receiving 7.6k citations
Hit Papers
Peers
Comparison fields: 5 of 144
- Cognitive Neuroscience 4.5k
- Statistical and Nonlinear Physics 1.7k
- Condensed Matter Physics 1.6k
- Artificial Intelligence 3.1k
- Cellular and Molecular Neuroscience 1.4k
Countries citing papers authored by Daniel J. Amit
This map shows the geographic impact of Daniel J. Amit'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 J. Amit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel J. Amit more than expected).
Fields of papers citing papers by Daniel J. Amit
This network shows the impact of papers produced by Daniel J. Amit. 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 J. Amit. The network helps show where Daniel J. Amit may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Daniel J. Amit, 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 | 2008 | 16 | |
| 2 | 2007 | 2 | |
| 3 | 2006 | 11 | |
| 4 | 2006 | 28 | |
| 5 | 2005 | 33 | |
| 6 | Field Theory, the Renormalization Group, and Critical Phenomenabreakdown → | 2005 | 530 |
| 7 | 2004 | 14 | |
| 8 | 2001 | 8 | |
| 9 | 1998 | 26 | |
| 10 | 1997 | 3 | |
| 11 | 1995 | 279 | |
| 12 | 1995 | 4 | |
| 13 | 1990 | 5 | |
| 14 | 1990 | 21 | |
| 15 | 1990 | 18 | |
| 16 | Modeling Brain Functionbreakdown → | 1989 | 444 |
| 17 | Spin-glass models of neural networksbreakdown → | 1985 | 733 |
| 18 | 1983 | 190 | |
| 19 | 1973 | 8 | |
| 20 | 1969 | 3 |
About Daniel J. Amit
Daniel J. Amit is a scholar working on Cognitive Neuroscience, Condensed Matter Physics and Statistical and Nonlinear Physics, having authored 84 papers that have together received 8.0k indexed citations. Recurring topics across this work include Neural dynamics and brain function (51 papers), Advanced Memory and Neural Computing (32 papers), Neural Networks and Applications (32 papers), Theoretical and Computational Physics (15 papers), Neuroscience and Neuropharmacology Research (8 papers), stochastic dynamics and bifurcation (6 papers), Black Holes and Theoretical Physics (5 papers) and Advanced Thermodynamics and Statistical Mechanics (5 papers). The work is most often cited by research in Cognitive Neuroscience (4.5k citations), Statistical and Nonlinear Physics (1.7k citations) and Condensed Matter Physics (1.6k citations). Daniel J. Amit has collaborated with scholars based in Israel, Italy and United States. Frequent co-authors include Haim Sompolinsky, Hanoch Gutfreund, Misha Tsodyks, V. Martı́n-Mayor, Stefano Fusi, Luca Peliti, Gianluigi Mongillo, Nicolas Brunel, Giorgio Parisi and Meir Griniasty. Their work appears in journals such as Network Computation in Neural Systems, Neural Computation, Nuclear Physics B, Annals of Physics and Journal of Statistical Physics.
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.