Sep 20, 2023 · Drift Control of High-Dimensional RBM: A Computational Method Based on Neural Networks. Authors:Baris Ata, J. Michael Harrison, Nian Si.

Sep 17, 2023 · Code for “actor-critic method for high dimensional static hamilton–jacobi–bellman partial differential equations based on neural networks”.

Drift Control of High-Dimensional RBM: A Computational Method Based on Neural Networks ... based computational method that relies heavily on deep neural network ...

RBMSolver. Drift Control of High-Dimensional RBM: A Computational Method Based on Neural Networks. requirement: Numpy and Tensorflow 2. Usage: python3 main.py ...

Drift Control of High-Dimensional RBM: A Computational Method Based on Neural Networks ... Efficient Steady-state Simulation of High-dimensional Stochastic ...

Efficient steady-state simulation of high-dimensional stochastic networks ... Drift control of high-dimensional rbm: A computational method based on neural ...

Efficient steady-state simulation of high-dimensional stochastic networks ... Drift control of high-dimensional rbm: A computational method based on neural ...

Drift Control of High-Dimensional RBM: A Computational Method Based on Neural Networks ... Motivated by applications in queueing theory, we consider a stochastic ...

Title: Drift control of high-dimensional RBM: A computational method based on neural networks. Abstract: We consider a stochastic control problem whose state ...