6 citations · 10 across the 5 of their papers we have counts for
11 papers
Forecasting Unobserved Node States with spatio-temporal Graph Neural Networks
Andreas Roth, Thomas Liebig
Forecasting future states of sensors is key to solving tasks like weather prediction, route planning, and many others when dealing with networks of sensors. But complete spatial co…
Certified Data Removal in Sum-Product Networks
Alexander Becker, Thomas Liebig
Data protection regulations like the GDPR or the California Consumer Privacy Act give users more control over the data that is collected about them. Deleting the collected data is…
Evaluating Machine Unlearning via Epistemic Uncertainty
Alexander Becker, Thomas Liebig
There has been a growing interest in Machine Unlearning recently, primarily due to legal requirements such as the General Data Protection Regulation (GDPR) and the California Consu…
Towards Truck Parking Lot Occupancy Estimation
Florian Ziegler, Maurice Freund, Andreas Rydzek +1
Occupied truck parking lots regularly cause hazardous situations. Estimation of current parking lot state could be utilized to provide drivers parking recommendations. In this work…
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures
Xiaoting Shao, Alejandro Molina, Antonio Vergari +4
Probabilistic graphical models are a central tool in AI; however, they are generally not as expressive as deep neural models, and inference is notoriously hard and slow. In contras…
Charging control of electric vehicles using contextual bandits considering the electrical distribution grid
Christian Römer, Johannes Hiry, Chris Kittl +2
With the proliferation of electric vehicles, the electrical distribution grids are more prone to overloads. In this paper, we study an intelligent pricing and power control mechani…