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Found 4 papers, 1 papers with code
Unsupervised Driving Event Discovery Based on Vehicle CAN-data
With our approach, we evaluate the applicability of recent time series-related contrastive and generative SSL techniques to learn representations that distinguish driving events.
Unsupervised 4D LiDAR Moving Object Segmentation in Stationary Settings with Multivariate Occupancy Time Series
In this work, we address the problem of unsupervised moving object segmentation (MOS) in 4D LiDAR data recorded from a stationary sensor, where no ground truth annotations are involved.
Enhancing Privacy via Hierarchical Federated Learning
Federated learning suffers from several privacy-related issues that expose the participants to various threats.
Cryptography and Security
On computable abstractions (a conceptual introduction)
This paper introduces abstractions that are meaningful for computers and that can be built and used according to computers' own criteria, i. e., computable abstractions.
