Jean‐Philippe Pellet
- Artificial Intelligence top 10%
- Computer Science Applications top 5%
- Information Systems top 10%
- Management Science and Operations Research top 10%
- Computational Theory and Mathematics
- Co-authors
- André ElisseeffFrancesco MondadaIsabelle GuyonPeter SpirtesMorgane ChevalierAlexander StatnikovGregory M. CooperLaila El‐Hamamsy
- Topics
- Bayesian Modeling and Causal Inference (5 papers)Teaching and Learning Programming (4 papers)Mathematics Education and Teaching Techniques (1 paper)
- Cited by
- Computer Science ApplicationsArtificial IntelligenceManagement Science and Operations Research
- Journals
- Computers & EducationJournal of Machine Learning ResearchIBM Journal of Research and Development
- Partner nations
- SwitzerlandFranceUnited States
In The Last Decade
Jean‐Philippe Pellet
14 papers receiving 280 citations
Peers
Comparison fields: 5 of 78
- Artificial Intelligence 149
- Computer Science Applications 76
- Information Systems 53
- Management Science and Operations Research 39
- Computational Theory and Mathematics 34
Countries citing papers authored by Jean‐Philippe Pellet
This map shows the geographic impact of Jean‐Philippe Pellet'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 Jean‐Philippe Pellet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jean‐Philippe Pellet more than expected).
Fields of papers citing papers by Jean‐Philippe Pellet
This network shows the impact of papers produced by Jean‐Philippe Pellet. 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 Jean‐Philippe Pellet. The network helps show where Jean‐Philippe Pellet may publish in the future.
Co-authorship network of co-authors of Jean‐Philippe Pellet
This figure shows the co-authorship network connecting the top 25 collaborators of Jean‐Philippe Pellet. A scholar is included among the top collaborators of Jean‐Philippe Pellet 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 Jean‐Philippe Pellet. Jean‐Philippe Pellet is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 46 | |
| 5 | 36 | |
| 6 | Three New Pillars of Digital Education | 1 |
| 7 | How beginner-friendly is a programming language? A short analysis based on Java and Python examples | 3 |
| 8 | 1 | |
| 9 | Predicting Graduate-level Performance from Undergraduate Achievements. | 15 |
| 10 | Development Projects for the CausalityWorkbench | 1 |
| 11 | 2 | |
| 12 | Using Markov Blankets for Causal Structure Learning | 130 |
| 13 | Finding Latent Causes in Causal Networks: an Efficient Approach Based on Markov Blankets | 12 |
| 14 | Design and Analysis of the Causation and Prediction Challenge | 45 |
About Jean‐Philippe Pellet
Jean‐Philippe Pellet is a scholar working on Computer Science Applications, Software and Artificial Intelligence, having authored 14 papers that have together received 299 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (5 papers), Teaching and Learning Programming (4 papers) and Mathematics Education and Teaching Techniques (1 paper). The work is most often cited by research in Computer Science Applications (76 citations), Artificial Intelligence (149 citations) and Management Science and Operations Research (39 citations). Jean‐Philippe Pellet has collaborated with scholars based in Switzerland, France and United States. Frequent co-authors include André Elisseeff, Francesco Mondada, Isabelle Guyon, Peter Spirtes, Morgane Chevalier, Alexander Statnikov, Gregory M. Cooper, Laila El‐Hamamsy, Christian Giang and Bernard Baumberger. Their work appears in journals such as Computers & Education, Journal of Machine Learning Research and IBM Journal of Research and Development.
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.