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Eamonn Bell
Eamonn Bell is Assistant Professor in the Department of Computer Science, at Durham University. His research interests include the history of technology as it relates to musical production and consumption in the twentieth century, with a focus on the uses of digital computers in the period between about 1955 and 1970, the application of mathematical and contemporary computational techniques to solve problems in musicology and music theory, and the visualization of musical data.
Latest posts
Bulk downloading from Dataverse
Today I wanted to download a dataset called DeepPatent2 Wu, Jian, 2023, “Replication Data for DeepPatent2: A Large-Scale Benchmarking Corpus for Technical Drawing Understanding”, https://doi.org/10.7910/DVN/UG4SBD, Harvard Dataverse, V2, UNF:6:v+kPnjPdsW7S36aUW0I7bg== [fileUNF] It’s hosted on Harvard’s Dataverse instance: Replication Data for DeepPatent2: A Large-Scale Benchmarking Corpus for Technical Drawing Understanding – Harvard Dataverse. The dataset is sharded into […]
Announcing “Accelerating embedded computational analysis of Web data about music in UK universities”
I am pleased to announce that the AHRC-funded project, “Accelerating embedded computational analysis of Web data about music in UK universities” is starting soon. We will begin with a series of trainings for workshop leaders in the Software Carpentries methodology. We will also soon circulate a survey to music researchers based in the UK to […]
Excerpt from Moles, Art et ordinateur (Casterman, 1971)
Translation: Eamonn Bell (rev. November 2022) [pp. 94-95] 1) The postulated existence of structural atoms, or of morphemes, semantemes, graphemes, mythemes etc. according to the terminology of Levi-Strauss is an affirmation of the structuralist principle conceived of as an atomic theory of the human sciences, and is applied here more specifically to art. The Theory […]
AI research and waiting
I’ve often thought it would be interesting to study what developers do while their code is waiting to compile. The complexities of the software tooling behind machine learning research have recently introduced a considerable amount of waiting around. This does not always involve waiting for compiling (although it often does). Rather, it relates to waiting […]