This map shows the geographic impact of Tillman Weyde'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 Tillman Weyde with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tillman Weyde more than expected).
This network shows the impact of papers produced by Tillman Weyde. 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 Tillman Weyde. The network helps show where Tillman Weyde may publish in the future.
Co-authorship network of co-authors of Tillman Weyde
This figure shows the co-authorship network connecting the top 25 collaborators of Tillman Weyde.
A scholar is included among the top collaborators of Tillman Weyde 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 Tillman Weyde. Tillman Weyde is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Confalonieri, Roberto, Tarek R. Besold, Tillman Weyde, et al.. (2019). What makes a good explanation? Cognitive dimensions of explaining intelligent machines.. Digital Commons - Michigan Tech (Michigan Technological University). 25–26.8 indexed citations
7.
Confalonieri, Roberto, et al.. (2019). An Ontology-based Approach to Explaining Artificial Neural Networks.. arXiv (Cornell University).12 indexed citations
Weyde, Tillman, et al.. (2016). Accuracy and interpretability trade-offs in machine learning applied to safer gambling. City Research Online (City University London).11 indexed citations
Tran, Son N., Daniel Wolff, Tillman Weyde, & Artur d’Avila Garcez. (2014). Feature Preprocessing with Restricted Boltzmann Machines for Music Similarity Learning. Figshare.1 indexed citations
Ng, Kia, Tillman Weyde, & Paolo Nesi. (2009). I-MAESTRO: TECHNOLOGY-ENHANCED LEARNING FOR MUSIC. The Journal of the Abraham Lincoln Association. 2008.5 indexed citations
16.
Ng, Kia, et al.. (2008). Interactive Multimedia Technology-Enhanced Learning for Music with i-Maestro. EdMedia: World Conference on Educational Media and Technology. 2008(1). 5673–5678.1 indexed citations
17.
Weyde, Tillman, et al.. (2007). A Systemic Approach to Music Performance Learning with Multimodal Technology Support. E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. 2007(1). 6654–6663.8 indexed citations
Weyde, Tillman, et al.. (2003). Structure recognition on sequences with a neuro-fuzzy-system.. European Society for Fuzzy Logic and Technology Conference. 386–391.1 indexed citations
20.
Weyde, Tillman. (2001). Grouping, Similarity and the Recognition of Rhythmic Structure. The Journal of the Abraham Lincoln Association.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.