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Machine learning models typically focus on specific targets like creating classifiers, often based on known population feature distributions in a business context. However, models calculating individual features adapt over time to improve…

Machine Learning · Computer Science 2024-02-23 Emanuele Luzio , Moacir Antonelli Ponti , Christian Ramirez Arevalo , Luis Argerich

The mathematical - numerical analysis of a discrete dynamical model with two independent delays was performed. Such model may describe a continuous system with delays that have real rational number values. Applicable characteristic…

Chaotic Dynamics · Physics 2026-02-10 Marek Berezowski , Ewa Fudala

Model selection methods are used in different scientific contexts to represent a characteristic data set in terms of a reduced number of parameters. Apparently, these methods have not found their way into the literature on multibody systems…

Robotics · Computer Science 2017-05-30 Javier Ros , Xabier Iriarte , Aitor Plaza , Vicente Mata

This work focuses on the question of how identifiability of a mathematical model, that is, whether parameters can be recovered from data, is related to identifiability of its submodels. We look specifically at linear compartmental models…

Algebraic Geometry · Mathematics 2019-05-27 Elizabeth Gross , Heather A. Harrington , Nicolette Meshkat , Anne Shiu

This article gives a brief overview of some recent progress in the characterization and parametrization of density matrices of finite dimensional systems. We discuss in some detail the Bloch-vector and Jarlskog parametrizations and mention…

Quantum Physics · Physics 2015-05-27 E. Brüning , H. Mäkelä , A. Messina , F. Petruccione

Machine learning (ML) and deep learning models are extensively used for parameter optimization and regression problems. However, not all inverse problems in ML are ``identifiable,'' indicating that model parameters may not be uniquely…

Machine Learning · Computer Science 2023-07-24 Reza Sameni

The time-dependent fields obtained by solving partial differential equations in two and more dimensions quickly overwhelm the analytical capabilities of the human brain. A meaningful insight into the temporal behaviour can be obtained by…

Numerical Analysis · Mathematics 2024-04-04 Miha Rot , Martin Horvat , Gregor Kosec

Parameter inference is a fundamental problem in data-driven modeling. Given observed data that is believed to be a realization of some parameterized model, the aim is to find parameter values that are able to explain the observed data. In…

Data Structures and Algorithms · Computer Science 2016-04-20 Carlo Albert , Simone Ulzega , Ruedi Stoop

The stochastic limit approximation method for ``rapid'' decay is presented, where the damping rate \gamma is comparable to the system frequency \Omega, i.e., \gamma \sim \Omega, whereas the usual stochastic limit approximation is applied…

Quantum Physics · Physics 2016-09-08 Gen Kimura , Kazuya Yuasa , Kentaro Imafuku

Distributed lag models (DLMs) express the cumulative and delayed dependence between pairs of time-indexed response and explanatory variables. In practical application, users of DLMs examine the estimated influence of a series of lagged…

Applications · Statistics 2018-01-23 Alastair Rushworth

We prove identifiability of parameters for a broad class of random graph mixture models. These models are characterized by a partition of the set of graph nodes into latent (unobservable) groups. The connectivities between nodes are…

Statistics Theory · Mathematics 2010-06-07 Elizabeth S. Allman , Catherine Matias , John A. Rhodes

This work is devoted to modelling and identification of the dynamics of the inter-sectoral balance of a macroeconomic system. An approach to the problem of specification and identification of a weakly formalized dynamical system is…

Dynamical Systems · Mathematics 2019-08-14 Olena Kostylenko , Helena Sofia Rodrigues , Delfim F. M. Torres

An approach for the description of stochastic systems is derived. Some of the variables in the system are studied forward in time, others backward in time. The approach is based on a perturbation expansion in the strength of the coupling…

Statistical Mechanics · Physics 2021-08-04 Piero Olla

Existing theoretical stabilization results for linear, hyperbolic multi-dimensional problems are extended to the discretized multi-dimensional problems. In contrast to existing theoretical and numerical analysis in the spatially…

Optimization and Control · Mathematics 2024-10-30 Michael Herty , Kai Hinzmann , Siegfried Müller , Ferdinand Thein

Duality between estimation and control is a foundational concept in Control Theory. Most students learn about the elementary duality -- between observability and controllability -- in their first graduate course in linear systems theory.…

Optimization and Control · Mathematics 2024-10-10 Jin Won Kim , Prashant G. Mehta

This work uncovers the low-dimensional nature the complex dynamics of actuated separated flows. Namely, motivated by the problem of model-based predictive control of separated flows, we identify the requirements on a model-based observer…

Fluid Dynamics · Physics 2007-10-10 R. Krechetnikov , J. E. Marsden , H. M. Nagib

Two coupled two-level systems placed under external time-dependent magnetic fields are modeled by a general Hamiltonian endowed with a symmetry that enables us to reduce the total dynamics into two independent two-dimensional sub-dynamics.…

Quantum Physics · Physics 2016-09-20 R. Grimaudo , A. Messina , H. Nakazato

We investigate the discrimination of two candidates of an unknown parameter in quantum systems with continuous weak measurement, inspired by the application of hypothesis testing in distinguish-ing two Hamiltonians [Kiilerich and M{\o}lmer,…

Quantum Physics · Physics 2019-07-24 Beili Gong , Wei Cui

The objective of this article is to complete preliminary results concerning the time-minimal control of dissipative two-level quantum systems whose dynamics is governed by Lindblad equations. The extremal system is described by a…

Mathematical Physics · Physics 2016-11-17 B. Bonnard , M. Chyba , D. Sugny

Dual control addresses the trade-off between exploitation and exploration, where control inputs both regulate the system and generate informative data for estimation and identification. For certain problem classes, control and estimation…

Optimization and Control · Mathematics 2026-04-08 Tren Baltussen , Nathan P. Lawrence , Alexander Katriniok , Ali Mesbah , Maurice Heemels
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