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pro vyhledávání: '"Process state"'
Learning dynamical models from data is not only fundamental but also holds great promise for advancing principle discovery, time-series prediction, and controller design. Among various approaches, Gaussian Process State-Space Models (GPSSMs) have rec
Externí odkaz:
http://arxiv.org/abs/2411.14679
Autor:
Lilge, Sven, Barfoot, Timothy D.
Continuous-time batch state estimation using Gaussian processes is an efficient approach to estimate the trajectories of robots over time. In the past, relatively simple physics-motivated priors have been considered for such approaches, using assumpt
Externí odkaz:
http://arxiv.org/abs/2408.01333
We compute probabilistic controlled invariant sets for nonlinear systems using Gaussian process state space models, which are data-driven models that account for unmodeled and unknown nonlinear dynamics. We investigate the relationship between robust
Externí odkaz:
http://arxiv.org/abs/2407.11256
Autor:
Chapela-Campa, David, Dumas, Marlon
This paper addresses the following problem: Given a process model and an event log containing trace prefixes of ongoing cases of a process, map each case to its corresponding state (i.e., marking) in the model. This state computation operation is a b
Externí odkaz:
http://arxiv.org/abs/2409.05658
Publikováno v:
Equality, Diversity and Inclusion: An International Journal, 2024, Vol. 43, Issue 9, pp. 103-121.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/EDI-10-2023-0340
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In order for robots to safely navigate in unseen scenarios using learning-based methods, it is important to accurately detect out-of-training-distribution (OoD) situations online. Recently, Gaussian process state-space models (GPSSMs) have proven use
Externí odkaz:
http://arxiv.org/abs/2309.06655
The Gaussian process state-space model (GPSSM) has attracted extensive attention for modeling complex nonlinear dynamical systems. However, the existing GPSSM employs separate Gaussian processes (GPs) for each latent state dimension, leading to escal
Externí odkaz:
http://arxiv.org/abs/2309.01074
Akademický článek
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