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This paper illustrates novel methods for nonstationary time series modeling along with their applications to selected problems in neuroscience. These methods are semi-parametric in that inferences are derived by combining sequential…

Applications · Statistics 2010-11-03 Fabio Rigat , Jim Q. Smith

We investigate the use of alternative divergences to Kullback-Leibler (KL) in variational inference(VI), based on the Variational Dropout \cite{kingma2015}. Stochastic gradient variational Bayes (SGVB) \cite{aevb} is a general framework for…

Machine Learning · Statistics 2017-11-15 Bogdan Mazoure , Riashat Islam

It is shown that the classical book by von Neumann proposing dynamics of measured systems with "reduction (or collapse) of system's wave packet" contains also hints how to avoid this discontinuity in time evolution of the measured system…

Quantum Physics · Physics 2022-01-12 Pavel Bóna

Networks represent how the entities of a system are connected and can be partitioned differently, prompting ways to compare partitions. Common approaches for comparing network partitions include information-theoretic measures based on…

Social and Information Networks · Computer Science 2024-01-18 Christopher Blöcker , Ingo Scholtes

The book is structured into four main chapters. Chapter 1 introduces the foundational concepts of divergence measures, including the well-known Kullback-Leibler divergence and its limitations. It then presents a detailed exploration of…

Methodology · Statistics 2024-09-04 Shinto Eguchi

The problem of estimating the Kullback-Leibler divergence $D(P\|Q)$ between two unknown distributions $P$ and $Q$ is studied, under the assumption that the alphabet size $k$ of the distributions can scale to infinity. The estimation is…

Information Theory · Computer Science 2018-02-22 Yuheng Bu , Shaofeng Zou , Yingbin Liang , Venugopal V. Veeravalli

Variational quantum circuits have become a widely used tool for performing quantum machine learning (QML) tasks on labeled quantum states. In some specific tasks or for specific variational ans\"atze, one may perform measurements on a…

Quantum Physics · Physics 2026-01-14 Andrey Kardashin , Konstantin Antipin

Characterization of quantum systems from experimental data is a central problem in quantum science and technology. But which measurements should be used to gather data in the first place? While optimal measurement choices can be worked out…

Quantum Physics · Physics 2025-07-15 Jiaxin Huang , Yan Zhu , Giulio Chiribella , Ya-Dong Wu

The quantum state discrimination problem is to distinguish between non-orthogonal quantum states. This problem has many applications in quantum information theory, quantum communication and quantum cryptography. In this paper a quantum…

Quantum Physics · Physics 2021-02-25 Doha A. Rizk , Ahmed Younes

Discriminator Guidance has become a popular method for efficiently refining pre-trained Score-Matching Diffusion models. However, in this paper, we demonstrate that the standard implementation of this technique does not necessarily lead to…

Machine Learning · Computer Science 2025-06-12 Alexandre Verine , Ahmed Mehdi Inane , Florian Le Bronnec , Benjamin Negrevergne , Yann Chevaleyre

The dynamics of a kicked quantum system undergoing repeated measurements of momentum is investigated. A diffusive behavior is obtained even when the dynamics of the classical counterpart is not chaotic. The diffusion coefficient is…

Quantum Physics · Physics 2009-10-31 P. Facchi , S. Pascazio , A. Scardicchio

Quantum measurements are not deterministic. For this reason quantum measurements are repeated for a number of shots on identically prepared systems. The uncertainty in each measurement depends on the number of shots and the expected outcome…

Quantum Physics · Physics 2025-03-12 Pieter Thijs Eendebak

We derive exceedingly simple practical procedures revealing the quantum nature of states and measurements by the violation of classical upper bounds on the statistics of arbitrary measurements. Data analysis is minimum and definite…

Quantum Physics · Physics 2009-04-28 Ángel Rivas , Alfredo Luis

When sampling multi-modal probability distributions, correctly estimating the relative probability of each mode, even when the modes have been discovered and locally sampled, remains challenging. We test a simple reweighting scheme designed…

Statistics Theory · Mathematics 2026-02-17 Pierre Monmarché

Black box variational inference (BBVI) with reparameterization gradients triggered the exploration of divergence measures other than the Kullback-Leibler (KL) divergence, such as alpha divergences. In this paper, we view BBVI with…

Machine Learning · Statistics 2018-01-09 Robert Bamler , Cheng Zhang , Manfred Opper , Stephan Mandt

To characterize the Kullback-Leibler divergence and Fisher information in general parametrized hidden Markov models, in this paper, we first show that the log likelihood and its derivatives can be represented as an additive functional of a…

Statistics Theory · Mathematics 2023-03-15 Cheng-Der Fuh , Chu-Lan Michael Kao , Tianxiao Pang

We study the dynamics of classical and quantum systems undergoing a continuous measurement of position by schematizing the measurement apparatus with an infinite set of harmonic oscillators at finite temperature linearly coupled to the…

Quantum Physics · Physics 2008-11-26 Carlo Presilla , Roberto Onofrio , Marco Patriarca

This short note is on a property of the Kullback-Leibler (KL) divergence which indicates that independent Gaussian distributions minimize the KL divergence from given independent Gaussian distributions. The primary purpose of this note is…

Information Theory · Computer Science 2020-12-04 Song Fang , Quanyan Zhu

We derive a state dependent error-disturbance trade-off based on a statistical distance in the sequential measurements of a pair of noncommutative observables and experimentally verify the relation with a photonic qubit system. We…

Quantum Physics · Physics 2019-03-27 Ya-Li Mao , Zhi-Hao Ma , Rui-Bo Jin , Qi-Chao Sun , Shao-Ming Fei , Qiang Zhang , Jingyun Fan , Jian-Wei Pan

We consider the question whether electromagnetism can be derived from quantum physics of measurements. It turns out that this is possible, both for quantum and classical electromagnetism, if we use more recent innovations such as smearing…

Mathematical Physics · Physics 2017-01-18 Andreas Andersson
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