Zobrazeno 1 - 10
of 193 827
pro vyhledávání: '"gaussian process"'
In this paper, we propose a novel intrinsic wrapped Gaussian process regression model for response variable measured on Riemannian manifold. We apply the parallel transport operator to define an intrinsic covariance structure addressing a critical as
Externí odkaz:
http://arxiv.org/abs/2411.18989
Computer models are used as a way to explore complex physical systems. Stationary Gaussian process emulators, with their accompanying uncertainty quantification, are popular surrogates for computer models. However, many computer models are not well r
Externí odkaz:
http://arxiv.org/abs/2411.14690
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:
Ning, Jingyun, Behl, Madhur
Autonomous racing is gaining attention for its potential to advance autonomous vehicle technologies. Accurate race car dynamics modeling is essential for capturing and predicting future states like position, orientation, and velocity. However, accura
Externí odkaz:
http://arxiv.org/abs/2411.13755
Humans are exposed to complex mixtures of environmental pollutants rather than single chemicals, necessitating methods to quantify the health effects of such mixtures. Research on environmental mixtures provides insights into realistic exposure scena
Externí odkaz:
http://arxiv.org/abs/2411.10858
Cooperating autonomous underwater vehicles (AUVs) often rely on acoustic communication to coordinate their actions effectively. However, the reliability of underwater acoustic communication decreases as the communication range between vehicles increa
Externí odkaz:
http://arxiv.org/abs/2411.07933
Gaussian process are a widely-used statistical tool for conducting non-parametric inference in applied sciences, with many computational packages available to fit to data and predict future observations. We study the use of the Greta software for Bay
Externí odkaz:
http://arxiv.org/abs/2411.05556
We develop a generative model for the nuclear matter equation of state at zero net baryon density using the Gaussian Process Regression method. We impose first-principles theoretical constraints from lattice QCD and hadron resonance gas at high- and
Externí odkaz:
http://arxiv.org/abs/2410.22160
This paper studies the tracking problem of target with the partially unknown motion model by an active agent with bearing-only measurements using Gaussian process learning. To address this problem, a learning-planning-control framework is proposed. F
Externí odkaz:
http://arxiv.org/abs/2410.18669