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Related publications (31)

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Mutual information for low-rank even-order symmetric tensor estimation

Nicolas Macris, Jean François Emmanuel Barbier, Clément Dominique Luneau

We consider a statistical model for finite-rank symmetric tensor factorization and prove a single-letter variational expression for its asymptotic mutual information when the tensor is of even order. The proof applies the adaptive interpolation method orig ...

Oxford University Press2021

Adaptive Path Interpolation Method for Sparse Systems: Application to a Censored Block Model

Nicolas Macris, Jean François Emmanuel Barbier, Chun Lam Chan

Recently, a new adaptive path interpolation method has been developed as a simple and versatile scheme to calculate exactly the asymptotic mutual information of Bayesian inference problems defined on dense factor graphs. These include random linear and gen ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Entering the plasma agriculture field: An attempt to standardize protocols for plasma treatment of seeds

Ivo Furno, Alan Howling, Fabio Avino, Alexandra Waskow

Plasma treatments are currently being assessed as a seed processing technology for agricultural purposes. There is sufficient information as a proof-of-concept, but a lack of standardization in the methodology prevents a convincing evaluation of plasma tre ...

2022

Weakly Supervised Deep Learning Methods for Biomicroscopy

Adrian Shajkofci

Optical microscopy, an invaluable tool in biology and medicine to observe and quantify cellular function, organ development, or disease mechanisms, requires constant trade-offs between spatial, temporal, and spectral resolution, invasiveness, acquisition t ...

EPFL2021

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

Towards Quantum 3D Imaging Devices

Edoardo Charbon, Claudio Bruschini, Samuel Burri, Arin Can Ülkü, Paul Mos, Michael Alan Wayne

We review the advancement of the research toward the design and implementation of quantum plenoptic cameras, radically novel 3D imaging devices that exploit both momentum–position entanglement and photon–number correlations to provide the typical refocusin ...

2021

A new spatial count data model with Bayesian additive regression trees for accident hot spot identification

Rico Krüger

The identification of accident hot spots is a central task of road safety management. Bayesian count data models have emerged as the workhorse method for producing probabilistic rankings of hazardous sites in road networks. Typically, these methods assume ...

2020

Identification of blowing snow particles in images from a Multi-Angle Snowflake Camera

Alexis Berne, Christophe Praz, Mathieu Oscar Schaer

A new method to automatically discriminate between hydrometeors and blowing snow particles on MultiAngle Snowflake Camera (MASC) images is introduced. The method uses four selected descriptors related to the image frequency, the number of particles detecte ...

2020

Robust Generalization via f−Mutual Information

Michael Christoph Gastpar, Amedeo Roberto Esposito, Ibrahim Issa

Given two probability measures P and Q and an event E, we provide bounds on P(E) in terms of Q(E) and f-divergences. In particular, the bounds are instantiated when the measures considered are a joint distribution and the corresponding product of marginals ...

IEEE2020

Lactate measurement by neurochemical profiling in the dorsolateral prefrontal cortex at 7T: accuracy, precision, and relaxation times

Pierre Magistretti, Lijing Xin, Masoumeh Dehghani Moghadam

Purpose This assesses the potential of measuring lactate in the human brain using three non-editing MRS methods at 7T and compares the accuracy and precision of the methods. Methods H-1 MRS data were measured in the right dorsolateral prefrontal cortex usi ...

Wiley2020

Inference on the Angular Distribution of Extremes

Claudio Andri Semadeni

The spectral distribution plays a key role in the statistical modelling of multivariate extremes, as it defines the dependence structure of multivariate extreme-value distributions and characterizes the limiting distribution of the relative sizes of the co ...

EPFL2020