74 citations · 155 across the 16 of their papers we have counts for
3 papers · 1 filter
Constrained Latent Action Policies for Model-Based Offline Reinforcement Learning
Marvin Alles, Philip Becker-Ehmck, Patrick van der Smagt +1
In offline reinforcement learning, a policy is learned using a static dataset in the absence of costly feedback from the environment. In contrast to the online setting, only using…
Adapting Deep Variational Bayes Filter for Enhanced Confidence Estimation in Finite Element Method Integrated Networks (FEMIN)
Simon Thel, Lars Greve, Maximilian Karl +1
The Finite Element Method (FEM) is a widely used technique for simulating crash scenarios with high accuracy and reliability. To reduce the significant computational costs associat…
Overcoming Knowledge Barriers: Online Imitation Learning from Visual Observation with Pretrained World Models
Xingyuan Zhang, Philip Becker-Ehmck, Patrick van der Smagt +1
Pretraining and finetuning models has become increasingly popular in decision-making. But there are still serious impediments in Imitation Learning from Observation (ILfO) with pre…