Results 11 to 20 of about 62,953 (258)
Dynamics of the Fisher information metric [PDF]
11 ...
Calmet, X., Calmet, J.
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Riemannian Laplace Approximation with the Fisher Metric
AISTATS 2024, with additional fixes and improvements.
Yu, Hanlin +4 more
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Curve Registration of Functional Data for Approximate Bayesian Computation
Approximate Bayesian computation is a likelihood-free inference method which relies on comparing model realisations to observed data with informative distance measures.
Anthony Ebert +3 more
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Holographic Fisher information metric in Schrödinger spacetime [PDF]
Minor ...
H. Dimov +4 more
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Fisher Information as General Metrics of Quantum Synchronization
Quantum synchronization has emerged as a crucial phenomenon in quantum nonlinear dynamics with potential applications in quantum information processing. Multiple measures for quantifying quantum synchronization exist. However, there is currently no widely agreed metric that is universally adopted.
Yuan Shen +3 more
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A Fisher-Rao Metric for Paracatadioptric Images of Lines [PDF]
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Stephen J. Maybank +2 more
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Solving an Integral Equation via Tricomplex-Valued Controlled Metric Spaces
In this present study, we propose the concept of tricomplex-controlled metric spaces as a generalization of both controlled metric-type spaces and tricomplex metric-type spaces.
Rajagopalan Ramaswamy +4 more
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The Fisher metric as a metric on the cotangent bundle
Abstract The Fisher metric on a manifold of probability distributions is usually treated as a metric on the tangent bundle. In this paper, we focus on the metric on the cotangent bundle induced from the Fisher metric with calling it the Fisher co-metric.
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We extend the speed limit of a distance between two states evolving by different generators for quantum systems [K. Suzuki and K. Takahashi, Phys. Rev. Res.
Kazutaka Takahashi, Yasuhiro Utsumi
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Characterizing (non-)Markovianity through Fisher information
A non-isolated physical system typically loses information to its environment, and when such loss is irreversible the evolution is said to be Markovian.
Paolo Abiuso, Matteo Scandi, Dario De Santis, Jacopo Surace
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