David Balduzzi
- Artificial Intelligence top 2%
- Domain Adaptation and Few-Shot Learning 5
- Adversarial Robustness in Machine Learning 3
- Neural Networks and Applications 3
- Machine Learning and ELM 2
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- Human Pose and Action Recognition 2
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function 6
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- Advanced Memory and Neural Computing 3
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- Game Theory and Applications 2
- Co-authors
- Giulio TononiMuhammad GhifaryW. Bastiaan KleijnMengjie ZhangManuel Gomez-RodriguezJure LeskovecBernhard SchölkopfBrian McWilliams
- Journals
- PLoS Computational Biology (2 papers)Digestive and Liver Disease (1 paper)Theory in Biosciences (1 paper)
- Partner nations
- United StatesNew ZealandGermany
In The Last Decade
David Balduzzi
26 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 126
- Artificial Intelligence 705
- Computer Vision and Pattern Recognition 438
- Cognitive Neuroscience 338
- Statistical and Nonlinear Physics 132
- Computational Mathematics 3
Countries citing papers authored by David Balduzzi
This map shows the geographic impact of David Balduzzi'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 David Balduzzi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Balduzzi more than expected).
Fields of papers citing papers by David Balduzzi
This network shows the impact of papers produced by David Balduzzi. 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 David Balduzzi. The network helps show where David Balduzzi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside David Balduzzi, 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 | 2020 | 2 | |
| 2 | From Chaos to Order: Symmetry and Conservation Laws in Game Dynamics | 2020 | 2 |
| 3 | Open-ended learning in symmetric zero-sum games | 2019 | 2 |
| 4 | 2019 | 6 | |
| 5 | The Mechanics of n-Player Differentiable Games | 2018 | 13 |
| 6 | Re-evaluating evaluation | 2018 | 3 |
| 7 | Scatter Component Analysis: A Unified Framework for Domain Adaptation and Domain Generalizationbreakdown → | 2016 | 323 |
| 8 | 2016 | 2 | |
| 9 | 2015 | 43 | |
| 10 | Domain Generalization for Object Recognition with Multi-task Autoencodersbreakdown → | 2015 | 339 |
| 11 | 2014 | 89 | |
| 12 | 2013 | 5 | |
| 13 | 2013 | 10 | |
| 14 | 2012 | 20 | |
| 15 | 2012 | 19 | |
| 16 | Information, learning and falsification | 2011 | 2 |
| 17 | 2011 | 3 | |
| 18 | 2009 | 151 | |
| 19 | 2008 | 235 | |
| 20 | 2006 | 7 |
About David Balduzzi
David Balduzzi is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Cognitive Neuroscience, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 26 papers that have together received 1.4k indexed citations. Recurring topics across this work include Neural dynamics and brain function (6 papers), Domain Adaptation and Few-Shot Learning (5 papers), Advanced Memory and Neural Computing (3 papers), Adversarial Robustness in Machine Learning (3 papers), Neural Networks and Applications (3 papers), Machine Learning and ELM (2 papers), Game Theory and Applications (2 papers) and Human Pose and Action Recognition (2 papers). The work is most often cited by research in Artificial Intelligence (705 citations), Computer Vision and Pattern Recognition (438 citations), Cognitive Neuroscience (338 citations), Statistical and Nonlinear Physics (132 citations) and Computational Mathematics (3 citations). David Balduzzi has collaborated with scholars based in United States, New Zealand and Germany. Frequent co-authors include Giulio Tononi, Muhammad Ghifary, W. Bastiaan Kleijn, Mengjie Zhang, Manuel Gomez-Rodriguez, Jure Leskovec, Bernhard Schölkopf, Brian McWilliams, Paolo Delvino and Gino Roberto Corazza. Their work appears in journals such as PLoS Computational Biology, Digestive and Liver Disease, Theory in Biosciences, Advances in Complex Systems and Network 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.