21 citations · 27 across the 30 of their papers we have counts for
6 papers · 1 filter
Clustered Randomized Smoothing for Stochastic Prediction Functions
Eduardo Figueiredo, Frederik Mathiesen, Julian Schumann +3
Modern stochastic predictors can model rich, multi-modal outcome distributions. However, this expressive power comes with challenges in ensuring robust predictions a critical r…
Emotion in an active inference model of human driving
Julian F. Schumann, Johan Engström, Ran Wei +3
Active inference has emerged as a principled framework for modeling adaptive behavior by balancing goal-directed action with uncertainty reduction. It has been successfully applied…
Set-Supervised Diffusion Policy: Learning Action-Chunking Diffusion through Corrections
Zhaoting Li, Gang Chen, Javier Alonso-Mora +2
Diffusion policies have recently emerged as a powerful framework for robotic manipulation. However, like other behavior cloning methods, they remain vulnerable to distributional sh…
Resolving space-sharing conflicts in road user interactions through uncertainty reduction: An active inference-based computational model
Julian F. Schumann, Johan Engström, Ran Wei +3
Understanding how road users resolve space-sharing conflicts is important both for traffic safety and the safe deployment of autonomous vehicles. While existing models have capture…
Evaluating randomized smoothing as a defense against adversarial attacks in trajectory prediction
Julian F. Schumann, Eduardo Figueiredo, Frederik Baymler Mathiesen +3
Accurate and robust trajectory prediction is essential for safe and efficient autonomous driving, yet recent work has shown that even state-of-the-art prediction models are highly…
Search Inspired Exploration in Reinforcement Learning
Georgios Sotirchos, Zlatan Ajanović, Jens Kober
Exploration in environments with sparse rewards remains a fundamental challenge in reinforcement learning (RL). Existing approaches such as curriculum learning and Go-Explore often…