1 citations · 1 across the 3 of their papers we have counts for
3 papers
Learning Latent Dynamics via Invariant Decomposition and (Spatio-)Temporal Transformers
Kai Lagemann, Christian Lagemann, Sach Mukherjee
We propose a method for learning dynamical systems from high-dimensional empirical data that combines variational autoencoders and (spatio-)temporal attention within a framework de…
Deep Learning of Causal Structures in High Dimensions
Kai Lagemann, Christian Lagemann, Bernd Taschler +1
Recent years have seen rapid progress at the intersection between causality and machine learning. Motivated by scientific applications involving high-dimensional data, in particula…
The Peregrine Falcon's Dive: On the Pull-Out Maneuver and Flight Control Through Wing-Morphing
Omar Selim, Erwin R. Gowree, Christian Lagemann +3
During the pull-out maneuver, Peregrine falcons were observed to adopt specific flight configurations which are thought to offer an aerodynamic advantage over aerial prey. Analysis…