Duration: 1:04:31
Posted: Jan 18, 2024

May 20, 2024 · ... deep neural network approximation is exponential. Paper · Add Code · A Mean-Field Optimal Control Formulation of Deep Learning · no code implementations • 3 Jul ...

Dec 4, 2023 · Many real world stochastic control problems suffer from the "curse of dimensionality". Paper · Add Code · A Mean-Field Optimal Control Formulation of Deep ...

May 15, 2024 · Li, A mean-field optimal control formulation of deep learning, Research in the Mathemat- · ical Sciences, 6:10 (2019). 40. L. Zhang, J. Han, H. Wang, W. Saidi, ...

Feb 2, 2024 · Abstract. We propose a deep learning approach to compute mean field control problems with individual noises. The problem consists of the Fokker-Planck (FP) ...

Dec 27, 2023 · A mean-field optimal control formulation of deep learning‏. E Weinan, J Han ... An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight ...

Nov 20, 2023 · In this paper, we propose several approaches to learn the optimal population-dependent controls in order to solve mean field control problems (MFC). Such ...

Sep 15, 2023 · MFGs are dynamic, symmetric games where the agents are indistinguishable but rational, meaning that their actions can affect the mean of the population. In the ...

Aug 15, 2023 · A Mean-Field Optimal Control Formulation of Deep Learning. Research in the Mathematical Sciences 2019, 6 (1), 10. (42) Zhang, C.; Li, Q.; Zhao, P ...

Oct 17, 2023 · We finally present instructive numerical experiments in Section 5, where solutions of the mean-field maximum principle are computed by means of a shooting.