Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
This map shows the geographic impact of Tom Diethe'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 Tom Diethe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom Diethe more than expected).
This network shows the impact of papers produced by Tom Diethe. 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 Tom Diethe. The network helps show where Tom Diethe may publish in the future.
Co-authorship network of co-authors of Tom Diethe
This figure shows the co-authorship network connecting the top 25 collaborators of Tom Diethe.
A scholar is included among the top collaborators of Tom Diethe 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 Tom Diethe. Tom Diethe is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Diethe, Tom, et al.. (2020). Bypassing Gradients Re-Projection with Episodic Memories in Online Continual Learning.. arXiv (Cornell University).1 indexed citations
7.
Diethe, Tom, et al.. (2020). Preserving Privacy in Analyses of Textual Data.. 1–3.2 indexed citations
8.
Chen, Yu, Tom Diethe, & Neil D. Lawrence. (2019). Facilitating Bayesian Continual Learning by Natural Gradients and Stein Gradients. Neural Information Processing Systems.5 indexed citations
9.
Diethe, Tom, et al.. (2019). Continual Learning in Practice. neural information processing systems.26 indexed citations
Diethe, Tom, et al.. (2016). ADL™: a topic model for discovery of activities of daily living in a smart home. International Joint Conference on Artificial Intelligence. 1404–1410.7 indexed citations
13.
Twomey, Niall, Tom Diethe, & Peter Flach. (2015). Bayesian Active Transfer Learning in Smart Homes, Advances in Active Learning: Bridging Theory and Practice. Bristol Research (University of Bristol).1 indexed citations
Smith, Graeme E., et al.. (2010). 2010 IEEE RADAR CONFERENCE.3 indexed citations
16.
Diethe, Tom, Simon Durrant, John Shawe‐Taylor, & Heinrich Neubauer. (2009). Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2009.9 indexed citations
17.
Diethe, Tom, et al.. (2009). Matching Pursuit Kernel Fisher Discriminant Analysis. Journal of Machine Learning Research. 5. 121–128.4 indexed citations
18.
Diethe, Tom, et al.. (2009). Sparse Multiview Methods for Classification of Musical Genre from Magnetoencephalography Recordings. UCL Discovery (University College London). 79–82.1 indexed citations
19.
Diethe, Tom & Peter J. Bentley. (2007). Advances in Artificial Life, Proceedings.1 indexed citations
20.
Diethe, Tom. (2005). Foundations of Augmented Cognition, Vol 11. International Conference on Human-Computer Interaction.2 indexed citations
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.