5 citations · 5 across the 4 of their papers we have counts for
5 papers
Does Physics Live in the Activations? Localizing Physical Quantities in Video Diffusion Models
Jonas Kneifl, Jakub Skalski, Bartłomiej Twardowski +1
Video generation models produce strikingly realistic sequences and are increasingly proposed as world models, yet recent benchmarks reveal pronounced deficits in their physical rea…
Data-driven identification of latent port-Hamiltonian systems
Johannes Rettberg, Jonas Kneifl, Julius Herb +3
Conventional physics-based modeling techniques involve high effort, e.g., time and expert knowledge, while data-driven methods often lack interpretability, structure, and sometimes…
VENI, VINDy, VICI: a generative reduced-order modeling framework with uncertainty quantification
Paolo Conti, Jonas Kneifl, Andrea Manzoni +4
The simulation of many complex phenomena in engineering and science requires solving expensive, high-dimensional systems of partial differential equations (PDEs). To circumvent thi…
On using Machine Learning Algorithms for Motorcycle Collision Detection
Philipp Rodegast, Steffen Maier, Jonas Kneifl +1
Globally, motorcycles attract vast and varied users. However, since the rate of severe injury and fatality in motorcycle accidents far exceeds passenger car accidents, efforts have…
Multi-Hierarchical Surrogate Learning for Structural Dynamical Crash Simulations Using Graph Convolutional Neural Networks
Jonas Kneifl, Jörg Fehr, Steven L. Brunton +1
Crash simulations play an essential role in improving vehicle safety, design optimization, and injury risk estimation. Unfortunately, numerical solutions of such problems using sta…