Seminar, Scientific Machine Learning

Kalenderhändelser saknas för aktuell period.

Kommande kalenderhändelser:

• Beverley McKeon: Data-driven descriptions of linear & nonlinear interactions in wall turbulence

  21 maj

  Seminar, Scientific Machine Learning

  tisdag 2024-05-21, 10.30 - 11.30

  Medverkande: Beverley McKeon (Stanford University)

  Plats: Digital Futures Hub, Osquars Backe 5, floor 2

  2024-05-21T10:30:00.000+02:00 2024-05-21T11:30:00.000+02:00 Beverley McKeon: Data-driven descriptions of linear & nonlinear interactions in wall turbulence (Seminar, Scientific Machine Learning) Digital Futures Hub, Osquars Backe 5, floor 2 (KTH, Stockholm, Sweden)Beverley McKeon: Data-driven descriptions of linear & nonlinear interactions in wall turbulence (Seminar, Scientific Machine Learning)

• Steve Brunton: Machine Learning for Scientific Discovery, with Examples in Fluid Mechanics

  23 maj

  Seminar, Scientific Machine Learning

  torsdag 2024-05-23, 10.30 - 11.30

  Medverkande: Steve Brunton (University of Washington)

  Plats: Digital Futures Hub, Osquars Backe 5, floor 2

  2024-05-23T10:30:00.000+02:00 2024-05-23T11:30:00.000+02:00 Steve Brunton: Machine Learning for Scientific Discovery, with Examples in Fluid Mechanics (Seminar, Scientific Machine Learning) Digital Futures Hub, Osquars Backe 5, floor 2 (KTH, Stockholm, Sweden)Steve Brunton: Machine Learning for Scientific Discovery, with Examples in Fluid Mechanics (Seminar, Scientific Machine Learning)

• Nathan Kutz: Deep Learning Architectures for Science and Engineering

  27 maj

  Seminar, Scientific Machine Learning

  måndag 2024-05-27, 10.30 - 11.30

  Medverkande: Nathan Kutz (University of Washington)

  Plats: Digital Futures Hub, Osquars Backe 5, floor 2

  2024-05-27T10:30:00.000+02:00 2024-05-27T11:30:00.000+02:00 Nathan Kutz: Deep Learning Architectures for Science and Engineering (Seminar, Scientific Machine Learning) Digital Futures Hub, Osquars Backe 5, floor 2 (KTH, Stockholm, Sweden)Nathan Kutz: Deep Learning Architectures for Science and Engineering (Seminar, Scientific Machine Learning)