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Showing 1–6 of 6 results
Advanced filters: Author: Christian Lagemann Clear advanced filters
  • Learning causal relationships between variables in large datasets is an outstanding challenge in various scientific applications. Lagemann et al. introduce a deep neural network approach combining convolutional and graph models intended for causal learning in high-dimensional biomedical problems.

    • Kai Lagemann
    • Christian Lagemann
    • Sach Mukherjee
    ResearchOpen Access
    Nature Machine Intelligence
    Volume: 5, P: 1306-1316
  • Transonic buffet is a ubiquitous challenge in commercial aviation since it can result in catastrophic structural failure of the aircraft wings. Here, authors experimentally show that this critical aerodynamic phenomenon can be mitigated using a carefully designed porous trailing edge on the wing.

    • Esther Lagemann
    • Steven L. Brunton
    • Christian Lagemann
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-15
  • Here, authors introduce SINDy-RL, a framework that combines sparse system identification with reinforcement learning to yield efficient, interpretable, and high-performing control policies.

    • Nicholas Zolman
    • Christian Lagemann
    • Steven L. Brunton
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-12
  • Particle image velocimetry is an imaging technique to determine the velocity components of flow fields, of use in a range of complex engineering problems including in environmental, aerospace and biomedical engineering. A recurrent neural network-based approach for learning displacement fields in an end-to-end manner is applied to this technique and achieves state-of-the-art accuracy and, moreover, allows generalization to new data, eliminating the need for traditional handcrafted models.

    • Christian Lagemann
    • Kai Lagemann
    • Wolfgang Schröder
    Research
    Nature Machine Intelligence
    Volume: 3, P: 641-651
  • Erwin Gowree et al. use wind tunnel experiments with life-sized models of the Peregrine falcon (Falco peregrinus) to investigate the aerodynamic basis for the bird’s complex aerobatics. They found that a vortex dominated flow enables the bird to perform high-speed maneouvres with minimal drag.

    • Erwin R. Gowree
    • Chetan Jagadeesh
    • Christoph Brücker
    ResearchOpen Access
    Communications Biology
    Volume: 1, P: 1-7
  • The standard current–phase relation in tunnel Josephson junctions involves a single sinusoidal term, but real junctions are more complicated. The effects of higher Josephson harmonics have now been identified in superconducting qubit devices.

    • Dennis Willsch
    • Dennis Rieger
    • Ioan M. Pop
    ResearchOpen Access
    Nature Physics
    Volume: 20, P: 815-821