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Found 8 papers, 0 papers with code
Efficient and passive learning of networked dynamical systems driven by non-white exogenous inputs
We present a regularized non-casual consistent estimator for this problem and analyze its sample complexity over two regimes: (a) where the interval $T$ consists of $n$ i. i. d.
Power Modeling for Effective Datacenter Planning and Compute Management
To the best of our knowledge, this is the largest scale power modeling study of this kind, in both the scope of diverse datacenter planning and real-time management use cases, as well as the variety of hardware configurations and workload types used for modeling and validation.
Estimating Linear Dynamical Networks of Cyclostationary Processes
The majority of prior work in consistent topology estimation relies on dynamical systems excited by temporally uncorrelated processes.
Hindering loads prompt clustered configurations that enhance stability during cargo transport by multiple Kinesin-1
Transport of intracellular cargo is often mediated by teams of molecular motors that function in a chaotic environment under varying conditions.
Physics Informed Topology Learning in Networks of Linear Dynamical Systems
Learning influence pathways of a network of dynamically related processes from observations is of considerable importance in many disciplines.
Learning the Exact Topology of Undirected Consensus Networks
In this article, we present a method to learn the interaction topology of a network of agents undergoing linear consensus updates in a non invasive manner.
Topology Estimation in Bulk Power Grids: Guarantees on Exact Recovery
For grids that include cycles of length three, we provide sufficient conditions that ensure existence of algorithms for exact reconstruction.
Exact Topology Reconstruction of Radial Dynamical Systems with Applications to Distribution System of the Power Grid
In this article we present a method to reconstruct the interconnectedness of dynamically related stochastic processes, where the interactions are bi-directional and the underlying topology is a tree.
