67 citations · 174 across the 4 of their papers we have counts for
4 papers
Enabling Dynamic and Intelligent Workflows for HPC, Data Analytics, and AI Convergence
Jorge Ejarque, Rosa M. Badia, Loïc Albertin +34
The evolution of High-Performance Computing (HPC) platforms enables the design and execution of progressively larger and more complex workflow applications in these systems. The co…
Intra-domain and cross-domain transfer learning for time series data -- How transferable are the features?
Erik Otović, Marko Njirjak, Dario Jozinović +3
In practice, it is very demanding and sometimes impossible to collect datasets of tagged data large enough to successfully train a machine learning model, and one possible solution…
SeisBench -- A Toolbox for Machine Learning in Seismology
Jack Woollam, Jannes Münchmeyer, Frederik Tilmann +10
Machine Learning (ML) methods have seen widespread adoption in seismology in recent years. The ability of these techniques to efficiently infer the statistical properties of large…
Local earthquakes detection: A benchmark dataset of 3-component seismograms built on a global scale
Fabrizio Magrini, Dario Jozinović, Fabio Cammarano +2
Machine learning is becoming increasingly important in scientific and technological progress, due to its ability to create models that describe complex data and generalize well. Th…