(…) “The discussion starts by reiterating on recent triumphs in weather and climate modeling, making connections to computer vision, physics-informed learning and neural operators. (…)”

...In this talk we explain the basic functioning of both methods and then present situations in which the methods provably work well, by identifying beneficial structures of the solutions of optimal control problems (...)"

🔗https://go.fau.de/1bddc

#FAU #movingKnowledge #FAUMoD #mathematik #maths

...where the objective of the optimization may range from stabilization of a set-point to energy efficiency to yield maximization.(...)

"Model Predictive Control #MPC and Reinforcement Learning #RL are two of the most prominent methods for computing control laws based on optimization. In both cases, the resulting controllers approximate infinite-horizon optimal controllers, ....

#MLPDES25 is possible thanks to the support
@humboldt-foundation.de
@faudcnavh.bsky.social
#poliba
#AFOSR

The #MLPDES25 workshop is an international event that brings together international researchers to explore the deepening connection between Machine Learning and Partial Differential Equations

#FAU #FAUMoD #movingKnowledge #Erlangen #Bavaria #Germany #Science #Research #workshop #NN #neuralNetworks