Litcius/Paper detail

Hybrid acceleration techniques for the physics-informed neural networks: a comparative analysis

F. A. Buzaev, Jiexing Gao, Ivan Chuprov, Evgeniy Kazakov

2023Machine Learning16 citationsDOIOpen Access PDF

Topics & Concepts

AccelerationArtificial neural networkComputer sciencePartial differential equationProcess (computing)LimitingArtificial intelligenceMathematicsPhysicsEngineeringMechanical engineeringMathematical analysisClassical mechanicsOperating systemModel Reduction and Neural NetworksFluid Dynamics and Turbulent FlowsMagnetic Properties and Applications
Hybrid acceleration techniques for the physics-informed neural networks: a comparative analysis | Litcius