Arthur Paul Jacot
- Artificial Intelligence
- Ecology, Evolution, Behavior and Systematics
- Computer Vision and Pattern Recognition
- Statistical and Nonlinear Physics
- Statistics and Probability
- Co-authors
- Clément HonglerMatthieu WyartStefano SpiglerMario GeigerGiulio BiroliLevent SagunStéphane d’AscoliFranck Gabriel
- Topics
- Neural Networks and Applications (4 papers)Generative Adversarial Networks and Image Synthesis (2 papers)Gaussian Processes and Bayesian Inference (2 papers)
- Journals
- Journal of Statistical Mechanics Theory and ExperimentInfoscience (Ecole Polytechnique Fédérale de Lausanne)arXiv (Cornell University)
- Partner nations
- SwitzerlandFrance
In The Last Decade
Arthur Paul Jacot
5 papers receiving 115 citations
Peers
Comparison fields: 5 of 53
- Artificial Intelligence 72
- Ecology, Evolution, Behavior and Systematics 23
- Computer Vision and Pattern Recognition 22
- Statistical and Nonlinear Physics 19
- Statistics and Probability 13
Countries citing papers authored by Arthur Paul Jacot
This map shows the geographic impact of Arthur Paul Jacot'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 Arthur Paul Jacot with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arthur Paul Jacot more than expected).
Fields of papers citing papers by Arthur Paul Jacot
This network shows the impact of papers produced by Arthur Paul Jacot. 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 Arthur Paul Jacot. The network helps show where Arthur Paul Jacot may publish in the future.
Co-authorship network of co-authors of Arthur Paul Jacot
This figure shows the co-authorship network connecting the top 25 collaborators of Arthur Paul Jacot. A scholar is included among the top collaborators of Arthur Paul Jacot based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Arthur Paul Jacot. Arthur Paul Jacot is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 27 | |
| 2 | 67 | |
| 3 | Disentangling feature and lazy learning in deep neural networks: an empirical study. | 3 |
| 4 | Freeze and Chaos for DNNs: an NTK view of Batch Normalization, Checkerboard and Boundary Effects. | 6 |
| 5 | Some Hawaiian Oribatoidea (Acarina) | 23 |
About Arthur Paul Jacot
Arthur Paul Jacot is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 5 papers that have together received 126 indexed citations. Recurring topics across this work include Neural Networks and Applications (4 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Gaussian Processes and Bayesian Inference (2 papers). The work is most often cited by research in Computational Mathematics (3 citations), Artificial Intelligence (72 citations) and Statistics and Probability (13 citations). Arthur Paul Jacot has collaborated with scholars based in Switzerland and France. Frequent co-authors include Clément Hongler, Matthieu Wyart, Stefano Spigler, Mario Geiger, Giulio Biroli, Levent Sagun, Stéphane d’Ascoli and Franck Gabriel. Their work appears in journals such as Journal of Statistical Mechanics Theory and Experiment, Infoscience (Ecole Polytechnique Fédérale de Lausanne) and arXiv (Cornell University).
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.