output
20212025
most citedTowards trustworthy multi-modal motion prediction: Holistic evaluation and interpretability of outputs

14 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

4 papers

cs.LG2025

Privacy Risks in Time Series Forecasting: User- and Record-Level Membership Inference

Nicolas Johansson, Tobias Olsson, Daniel Nilsson +2

Membership inference attacks (MIAs) aim to determine whether specific data were used to train a model. While extensively studied on classification models, their impact on time seri…

cs.CR2024

Evaluating lightweight unsupervised online IDS for masquerade attacks in CAN

Pablo Moriano, Steven C. Hespeler, Mingyan Li +1

Vehicular controller area networks (CANs) are susceptible to masquerade attacks by malicious adversaries. In masquerade attacks, adversaries silence a targeted ID and then send mal…

cs.RO2022★ 14 cited

Towards trustworthy multi-modal motion prediction: Holistic evaluation and interpretability of outputs

Sandra Carrasco Limeros, Sylwia Majchrowska, Joakim Johnander +3

Predicting the motion of other road agents enables autonomous vehicles to perform safe and efficient path planning. This task is very complex, as the behaviour of road agents depen…

cs.PL2021★ 13 cited

Compiling Universal Probabilistic Programming Languages with Efficient Parallel Sequential Monte Carlo Inference

Daniel Lundén, Joey Öhman, Jan Kudlicka +3

Probabilistic programming languages (PPLs) allow users to encode arbitrary inference problems, and PPL implementations provide general-purpose automatic inference for these problem…