Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators
Benedikt Alkin, J. Brandstetter, Andreas Fürst, Lukas Gruber, Markus Holzleitner, Simon Schmid
Topics & Concepts
ScalingComputer scienceArtificial neural networkAlgorithmMathematicsPhysicsOperator (biology)Artificial intelligenceRepresentation (politics)Theoretical computer scienceStatistical physicsAlgebra over a fieldKey (lock)Feature (linguistics)Context (archaeology)Theoretical physicsNoise (video)Neural Networks and Reservoir ComputingModel Reduction and Neural NetworksNeural Networks and Applications