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Stochastic Quantum Sampling for Non-Logconcave Distributions and Estimating Partition Functions
We also incorporate a stochastic gradient oracle that implements the quantum walk operators inexactly by only using mini-batch gradients.
Efficient Quantum Algorithms for Quantum Optimal Control
In this paper, we present efficient quantum algorithms that are exponentially faster than classical algorithms for solving the quantum optimal control problem.
The Mori-Zwanzig formulation of deep learning
We develop a new formulation of deep learning based on the Mori-Zwanzig (MZ) formalism of irreversible statistical mechanics.
Stability Preserving Data-driven Models With Latent Dynamics
In this paper, we introduce a data-driven modeling approach for dynamics problems with latent variables.
A Local Convergence Theory for the Stochastic Gradient Descent Method in Non-Convex Optimization With Non-isolated Local Minima
Loss functions with non-isolated minima have emerged in several machine learning problems, creating a gap between theory and practice.
Error Bounds of the Invariant Statistics in Machine Learning of Ergodic Itô Diffusions
We find that sufficient conditions for such a linear dependence result are through learning algorithms that produce a uniformly Lipschitz and consistent estimator in the hypothesis space that retains certain characteristics of the drift coefficients, such as the usual linear growth condition that guarantees the existence of solutions of the underlying SDEs.
Projection based model reduction for the immersed boundary method
Fluid-structure interactions are central to many bio-molecular processes, and they impose a great challenge for computational and modeling methods.
Numerical Analysis Numerical Analysis
