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Found 5 papers, 0 papers with code
Monte Carlo Tree Search based Hybrid Optimization of Variational Quantum Circuits
Variational quantum algorithms stand at the forefront of simulations on near-term and future fault-tolerant quantum devices.
Accelerating Primal-dual Methods for Regularized Markov Decision Processes
Entropy regularized Markov decision processes have been widely used in reinforcement learning.
Approximate Newton policy gradient algorithms
This paper proposes an approximate Newton method for the policy gradient algorithm with entropy regularization.
A semigroup method for high dimensional elliptic PDEs and eigenvalue problems based on neural networks
In this paper, we propose a semigroup method for solving high-dimensional elliptic partial differential equations (PDEs) and the associated eigenvalue problems based on neural networks.
A semigroup method for high dimensional committor functions based on neural network
This paper proposes a new method based on neural networks for computing the high-dimensional committor functions that satisfy Fokker-Planck equations.
