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Found 3 papers, 1 papers with code
Bayesian Identification of Nonseparable Hamiltonian Systems Using Stochastic Dynamic Models
This paper proposes a probabilistic Bayesian formulation for system identification (ID) and estimation of nonseparable Hamiltonian systems using stochastic dynamic models.
Dynamic multi-agent assignment via discrete optimal transport
We propose an optimal solution to a deterministic dynamic assignment problem by leveraging connections to the theory of discrete optimal transport to convert the combinatorial assignment problem into a tractable linear program.
Multiagent Systems Systems and Control Systems and Control Optimization and Control Computation 90C08, 49J15, 65K10
Gradient-based Optimization for Regression in the Functional Tensor-Train Format
We consider the task of low-multilinear-rank functional regression, i. e., learning a low-rank parametric representation of functions from scattered real-valued data.
