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The Fisher information $F$ gives a limit to the ultimate precision achievable in a phase estimation protocol. It has been shown recently that the Fisher information for a linear two-mode interferometer cannot exceed the number of particles…

We have calculated the Tsallis entropy and Fisher information matrix (entropy) of spatially-correlated nonextensive systems, by using an analytic non-Gaussian distribution obtained by the maximum entropy method. Effects of the correlated…

Statistical Mechanics · Physics 2009-11-13 Hideo Hasegawa

Catastrophic forgetting impairs the continuous learning of large language models. We propose Fisher-Guided Gradient Masking (FGGM), a framework that mitigates this by strategically selecting parameters for updates using diagonal Fisher…

Machine Learning · Computer Science 2026-01-27 Chao-Hong Tan , Qian Chen , Wen Wang , Yukun Ma , Chong Zhang , Chong Deng , Qinglin Zhang , Xiangang Li , Jieping Ye

Many statistical models require an estimation of unknown (co)-variance parameter(s) in a model. The estimation usually obtained by maximizing a log-likelihood which involves log determinant terms. In principle, one requires the…

Computation · Statistics 2016-09-05 Shengxin Zhu , Tongxiang Gu , Xiaowen Xu , Zeyao Mo

The choice of a time integration scheme is a crucial aspect of any transient fluid simulation, and Smoothed-Particle Hydrodynamics (SPH) is no exception. The influence of the time integration scheme on energy balance is here addressed. To…

The increasing integration of renewable energy sources has introduced complex dynamic behavior in power systems that challenge the adequacy of traditional continuous-time modeling approaches. These developments call for modeling frameworks…

Systems and Control · Electrical Eng. & Systems 2026-01-19 B. G. Odunlami , M. Netto , Y. Susuki

A hybrid (i.e., physics-guided data-driven) feedforward tracking controller is proposed for systems with unmodeled linear or nonlinear dynamics. The controller is based on the filtered basis function (FBF) approach, hence it is called a…

Systems and Control · Electrical Eng. & Systems 2022-06-27 Cheng-Hao Chou , Molong Duan , Chinedum E. Okwudire

Causal inference across multiple data sources offers a promising avenue to enhance the generalizability and replicability of scientific findings. However, data integration methods for time-to-event outcomes, common in biomedical research,…

Methodology · Statistics 2025-05-16 Yi Liu , Alexander W. Levis , Ke Zhu , Shu Yang , Peter B. Gilbert , Larry Han

The quantum Fisher information matrix is a central object in multiparameter quantum estimation theory. It is usually challenging to obtain analytical expressions for it because most calculation methods rely on the diagonalization of the…

Quantum Physics · Physics 2021-05-07 Lukas J. Fiderer , Tommaso Tufarelli , Samanta Piano , Gerardo Adesso

The modified Hunter--Saxton equation models the propagation of short capillary-gravity waves. As it involves a mixed derivative, its initial value problem on the periodic domain is much more complicated than the standard evolutionary…

Numerical Analysis · Mathematics 2018-02-13 Shun Sato

Stochastic hybrid systems combine continuous-time stochastic dynamics with discrete reset events, producing intrinsically non-Gaussian and often multimodal uncertainty. A consistent propagation law must also account for boundary-induced…

Systems and Control · Electrical Eng. & Systems 2026-05-21 Kaito Iwasaki , Tejaswi K. C. , Anthony Bloch , Maani Ghaffari , Taeyoung Lee

The quantum Fisher information matrix provides us with a tool to determine the precision, in any multiparametric estimation protocol, through quantum Cram\'er-Rao bound. In this work, we study simultaneous and individual estimation…

Quantum Physics · Physics 2019-04-17 L. Bakmou , A. Slaoui , M. Daoud , R. Ahl Laamara

Federated Learning (FL) has become increasingly popular across different sectors, offering a way for clients to work together to train a global model without sharing sensitive data. It involves multiple rounds of communication between the…

Machine Learning · Computer Science 2025-07-24 Amandeep Singh Bhatia , Sabre Kais

Variational time integrators are derived in the context of discrete mechanical systems. In this area, the governing equations for the motion of the mechanical system are built following two steps: (a) Postulating a discrete action; (b)…

Computational Physics · Physics 2018-05-04 Leandro Tavares da Silva , Gilson Antonio Giraldi

Two classically equivalent expressions of mutual information of probability distributions (classical bipartite states) diverge when extended to quantum systems, and this difference has been employed to define quantum discord, a quantifier…

Quantum Physics · Physics 2025-10-20 Huihui Li , Shunlong Luo , Yue Zhang

We show that the mathematical form of the information measure of Fisher's I for a Gibbs' canonical probability distribution (the most important one in statistical mechanics) incorporates important features of the intrinsic structure of…

Statistical Mechanics · Physics 2007-05-23 F. Pennini , A. Plastino

We present a hybrid computational method for simulating the dynamics of macromolecules in solution which couples a mesoscale solver for the fluctuating hydrodynamics (FH) equations with molecular dynamics to describe the macromolecule. The…

Soft Condensed Matter · Physics 2007-05-23 G. Giupponi , G. De Fabritiis , P. V. Coveney

We introduce Statistical Flow Matching (SFM), a novel and mathematically rigorous flow-matching framework on the manifold of parameterized probability measures inspired by the results from information geometry. We demonstrate the…

Machine Learning · Computer Science 2025-11-26 Chaoran Cheng , Jiahan Li , Jian Peng , Ge Liu

The Fisher Information Matrix formalism is extended to cases where the data is divided into two parts (X,Y), where the expectation value of Y depends on X according to some theoretical model, and X and Y both have errors with arbitrary…

Cosmology and Nongalactic Astrophysics · Physics 2015-02-20 A. F. Heavens , M. Seikel , B. D. Nord , M. Aich , Y. Bouffanais , B. A. Bassett , M. P. Hobson

Recent work showed that hybrid networks, which combine predefined and learnt filters within a single architecture, are more amenable to theoretical analysis and less prone to overfitting in data-limited scenarios. However, their performance…

Computer Vision and Pattern Recognition · Computer Science 2022-03-30 Dmitry Minskiy , Miroslaw Bober
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