28 citations · 28 across the 2 of their papers we have counts for
3 papers
Stochastic Concept Bottleneck Models
Moritz Vandenhirtz, Sonia Laguna, Ričards Marcinkevičs +1
Concept Bottleneck Models (CBMs) have emerged as a promising interpretable method whose final prediction is based on intermediate, human-understandable concepts rather than the raw…
Interpretable Models for Granger Causality Using Self-explaining Neural Networks
Ričards Marcinkevičs, Julia E. Vogt
Exploratory analysis of time series data can yield a better understanding of complex dynamical systems. Granger causality is a practical framework for analysing interactions in seq…
Discovery of Important Subsequences in Electrocardiogram Beats Using the Nearest Neighbour Algorithm
Ricards Marcinkevics, Steven Kelk, Carlo Galuzzi +1
The classification of time series data is a well-studied problem with numerous practical applications, such as medical diagnosis and speech recognition. A popular and effective app…