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Found 7 papers, 0 papers with code
Fully Decentralized Design of Initialization-free Distributed Network Size Estimation
In this paper, we propose a distributed scheme for estimating the network size, which refers to the total number of agents in a network.
Data-driven Discovery of Chemotactic Migration of Bacteria via Machine Learning
The resulting data-driven PDE can then be simulated to reproduce/predict computational or experimental bacterial density profile data, and estimate the underlying (unmeasured) chemonutrient field evolution.
Learning black- and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data
We exploit Automatic Relevance Determination (ARD) within a Gaussian Process framework for the identification of a parsimonious set of collective observables that parametrize the law of the effective PDEs.
Multi-armed Bandit Algorithm against Strategic Replication
We consider a multi-armed bandit problem in which a set of arms is registered by each agent, and the agent receives reward when its arm is selected.
Coarse-scale PDEs from fine-scale observations via machine learning
In this paper, we introduce a data-driven framework for the identification of unavailable coarse-scale PDEs from microscopic observations via machine learning algorithms.
Distributed Algorithm for Economic Dispatch Problem with Separable Losses
Economic dispatch problem for a networked power system has been considered.
Systems and Control
Linking Gaussian Process regression with data-driven manifold embeddings for nonlinear data fusion
In this paper, we will explore mathematical algorithms for multifidelity information fusion that use such an approach towards improving the representation of the high-fidelity function with only a few training data points.
