4 papers
Causal Mechanism Estimation in Multi-Sensor Systems Across Multiple Domains
Jingyi Yu, Tim Pychynski, Marco F. Huber
To gain deeper insights into a complex sensor system through the lens of causality, we present common and individual causal mechanism estimation (CICME), a novel three-step approac…
ViPro-2: Unsupervised State Estimation via Integrated Dynamics for Guiding Video Prediction
Patrick Takenaka, Johannes Maucher, Marco F. Huber
Predicting future video frames is a challenging task with many downstream applications. Previous work has shown that procedural knowledge enables deep models for complex dynamical…
ViPro: Enabling and Controlling Video Prediction for Complex Dynamical Scenarios using Procedural Knowledge
Patrick Takenaka, Johannes Maucher, Marco F. Huber
We propose a novel architecture design for video prediction in order to utilize procedural domain knowledge directly as part of the computational graph of data-driven models. On th…
Guiding Video Prediction with Explicit Procedural Knowledge
Patrick Takenaka, Johannes Maucher, Marco F. Huber
We propose a general way to integrate procedural knowledge of a domain into deep learning models. We apply it to the case of video prediction, building on top of object-centric dee…