Peter Flach
About
In The Last Decade
Peter Flach
213 papers receiving 20.2k citations
Hit Papers
Peers
Comparison fields: 5 of 224
- Artificial Intelligence 9.5k
- Computer Vision and Pattern Recognition 6.1k
- Information Systems 1.9k
- Signal Processing 1.4k
- Computational Theory and Mathematics 1.3k
Countries citing papers authored by Peter Flach
This map shows the geographic impact of Peter Flach'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 Peter Flach with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Flach more than expected).
Fields of papers citing papers by Peter Flach
This network shows the impact of papers produced by Peter Flach. 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 Peter Flach. The network helps show where Peter Flach may publish in the future.
Co-authorship network of co-authors of Peter Flach
This figure shows the co-authorship network connecting the top 25 collaborators of Peter Flach. A scholar is included among the top collaborators of Peter Flach 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 Peter Flach. Peter Flach is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 15 | |
| 4 | Machine Learning Explanations as Boundary Objects: How AI Researchers Explain and Non-Experts Perceive Machine Learning | 2 |
| 5 | Bypassing Gradients Re-Projection with Episodic Memories in Online Continual Learning. | 1 |
| 6 | Analysis of patient domestic activity in recovery from hip or knee replacement surgery: modelling wrist-worn wearable RSSI and accelerometer data in the wild | 3 |
| 7 | 100 | |
| 8 | Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence breakdown → | 570 |
| 9 | Machine learning and knowledge discovery in databases: ECML-PKDD Proceedings, Part II | 0 |
| 10 | Ukwabelana - An open-source morphological Zulu corpus | 15 |
| 11 | First-Order Logic. | 1 |
| 12 | UNGRADE: UNsupervised GRAph DEcomposition | 5 |
| 13 | PROMODES: A Probabilistic Generative Model for Word Decomposition. | 9 |
| 14 | Repairing concavities in ROC curves | 56 |
| 15 | An analysis of rule evaluation metrics | 51 |
| 16 | Improved data set characterisation for meta-learning | 9 |
| 17 | Web-based analysis of data mining and decision support education | 8 |
| 18 | WBCsvm: Weighted Bayesian Classification based on Support Vector Machines | 18 |
| 19 | A First-order Representation for Knowledge Discovery and Bayesian Classification on Relational Data | 1 |
| 20 | 100 |
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.