Publications related to Kullback–Leibler divergence

Many-body localization in a fragmented Hilbert space

We study many-body localization (MBL) in a pair-hopping model exhibiting strong fragmentation of the Hilbert space. We show that several Krylov subspaces have both ergodic statistics in the thermodynamic limit and a dimension that scales much slower than t ...

2021

Towards Interactions Through Differentiable-Non-Differentiable Scale Transitions In Scale Relativity Theory

Maria-Alexandra Paun

It is shown that, in the framework of Scale Relativity Theory, correlations of type informational entropy/cross entropy - probability density, in the description of the dynamics of any complex system, can be perceived as interactions. Explaining these inte ...

UNIV POLITEHNICA BUCHAREST, SCI BULL2021

Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts

Daniel Kuhn, Viet Anh Nguyen, Bahar Taskesen

Least squares estimators, when trained on a few target domain samples, may predict poorly. Supervised domain adaptation aims to improve the predictive accuracy by exploiting additional labeled training samples from a source distribution that is close to th ...

2021

Learning in Volatile Environments With the Bayes Factor Surprise

Wulfram Gerstner, Johanni Michael Brea, Alireza Modirshanechi, Vasiliki Liakoni

Surprise-based learning allows agents to rapidly adapt to nonstationary stochastic environments characterized by sudden changes. We show that exact Bayesian inference in a hierarchical model gives rise to a surprise-modulated trade-off between forgetting o ...

MIT PRESS2021

Validating model-based data interpretation methods for quantification of reserve capacity

Ian Smith, Sai Ganesh Sarvotham Pai

Optimal performance of civil infrastructure is an important aspect of liveable cities. A judicious combination of physics-based models with monitoring data in a validated methodology that accounts for uncertainties is explored in this paper. This methodolo ...

2021

Differential Entropy of the Conditional Expectation under Gaussian Noise

Michael Christoph Gastpar, Alper Köse, Ahmet Arda Atalik

This paper considers an additive Gaussian noise channel with arbitrarily distributed finite variance input signals. It studies the differential entropy of the minimum mean-square error (MMSE) estimator and provides a new lower bound which connects the diff ...

IEEE2021

Deep visual Re-identification with confidence

Alexandre Massoud Alahi, Sven Kreiss, George Adaimi

Transportation systems often rely on understanding the flow of vehicles or pedestrian. From traffic monitoring at the city scale, to commuters in train terminals, recent progress in sensing technology make it possible to use cameras to better understand th ...

2021

Bell Diagonal and Werner State Generation: Entanglement, Non-Locality, Steering and Discord on the IBM Quantum Computer

Nicolas Macris, Su Yeon Chang, Marc-André Dupertuis, Chun Lam Chan, Samuel Bosch, Nicolas Schwaller, Frédéric Gessler

We propose the first correct special-purpose quantum circuits for preparation of Bell diagonal states (BDS), and implement them on the IBM Quantum computer, characterizing and testing complex aspects of their quantum correlations in the full parameter spa ...

2021

Far field superlensing inside biological media through a nanorod lens using spatiotemporal information

Anja Skrivervik

Far field superlensing of light has generated great attention in optical focusing and imaging applications. The capability of metamaterials to convert evanescent waves to propagative waves has led to numerous proposals in this regard. The common drawback o ...

2021

Robust Generalization via $\alpha$-Mutual Information

Michael Christoph Gastpar, Amedeo Roberto Esposito, Ibrahim Issa

The aim of this work is to provide bounds connecting two probability measures of the same event using Rényi

\alpha

-Divergences and Sibson’s

\alpha

-Mutual Information, a generalization of respectively the Kullback-Leibler Divergence and Shannon’s Mutual ...

ETHZ2020

Kullback–Leibler divergence

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Many-body localization in a fragmented Hilbert space

Towards Interactions Through Differentiable-Non-Differentiable Scale Transitions In Scale Relativity Theory

Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts

Learning in Volatile Environments With the Bayes Factor Surprise

Validating model-based data interpretation methods for quantification of reserve capacity

Differential Entropy of the Conditional Expectation under Gaussian Noise

Deep visual Re-identification with confidence

Bell Diagonal and Werner State Generation: Entanglement, Non-Locality, Steering and Discord on the IBM Quantum Computer

Far field superlensing inside biological media through a nanorod lens using spatiotemporal information

Robust Generalization via $\alpha$-Mutual Information

Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts

Validating model-based data interpretation methods for quantification of reserve capacity

Differential Entropy of the Conditional Expectation under Gaussian Noise

Bell Diagonal and Werner State Generation: Entanglement, Non-Locality, Steering and Discord on the IBM Quantum Computer

Far field superlensing inside biological media through a nanorod lens using spatiotemporal information

Many-body localization in a fragmented Hilbert space

Towards Interactions Through Differentiable-Non-Differentiable Scale Transitions In Scale Relativity Theory

Learning in Volatile Environments With the Bayes Factor Surprise

Deep visual Re-identification with confidence

Robust Generalization via $\alpha$-Mutual Information