147 citations · 590 across the 30 of their papers we have counts for
3 papers · 1 filter
Fully Automatic Neural Network Reduction for Formal Verification
Tobias Ladner, Matthias Althoff
Formal verification of neural networks is essential before their deployment in safety-critical applications. However, existing methods for formally verifying neural networks are no…
Deep Occupancy-Predictive Representations for Autonomous Driving
Eivind Meyer, Lars Frederik Peiss, Matthias Althoff
Manually specifying features that capture the diversity in traffic environments is impractical. Consequently, learning-based agents cannot realize their full potential as neural mo…
Geometric Deep Learning for Autonomous Driving: Unlocking the Power of Graph Neural Networks With CommonRoad-Geometric
Eivind Meyer, Maurice Brenner, Bowen Zhang +3
Heterogeneous graphs offer powerful data representations for traffic, given their ability to model the complex interaction effects among a varying number of traffic participants an…