Publications related to Impact of Sample Sizes on Information Theoretic Measures for Audio-Visual Signal Processing

Mutual Information for the Stochastic Block Model by the Adaptive Interpolation Method

Nicolas Macris, Jean François Emmanuel Barbier, Chun Lam Chan

We rigorously derive a single-letter variational expression for the mutual information of the asymmetric two-groups stochastic block model in the dense graph regime. Existing proofs in the literature are indirect, as they involve mapping the model to a ran ...

IEEE2019

Recovering covariance from functional fragments

Victor Panaretos, Marie-Hélène Descary

We consider nonparametric estimation of a covariance function on the unit square, given a sample of discretely observed fragments of functional data. When each sample path is observed only on a subinterval of length , one has no statistical information on ...

2019

Robust T2 Relaxometry with Hamiltonian MCMC for Myelin Water Fraction Estimation

Jean-Philippe Thiran, Marco Pizzolato, Thomas Yu

We present a voxel-wise Bayesian multi-compartment T2 relaxometry fitting method based on Hamiltonian Markov Chain Monte Carlo (HMCMC) sampling. The T 2 spectrum is modeled as a mixture of truncated Gaussian components, which involves the estimation of par ...

IEEE2019

Database Alignment with Gaussian Features

Negar Kiyavash, Osman Emre Dai

We consider the problem of aligning a pair of databases with jointly Gaussian features. We consider two algorithms, complete database alignment via MAP estimation among all possible database alignments, and partial alignment via a thresholding approach of ...

MLR Press2019

Quantifying high-order interdependencies via multivariate extensions of the mutual information

Michael Christoph Gastpar, Fernando Rosas de Andraca

This paper introduces a model-agnostic approach to study statistical synergy, a form of emergence in which patterns at large scales are not traceable from lower scales. Our framework leverages various multivariate extensions of Shannon's mutual information ...

2019

The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

Fei Pu

In this thesis, we study systems of linear and/or non-linear stochastic heat equations and fractional heat equations in spatial dimension

1

driven by space-time white noise. The main topic is the study of hitting probabilities for the solutions to these ...

EPFL2018

Semiparametric Bayesian Risk Estimation for Complex Extremes

Thomas Lugrin

Extreme events are responsible for huge material damage and are costly in terms of their human and economic impacts. They strike all facets of modern society, such as physical infrastructure and insurance companies through environmental hazards, banking an ...

EPFL2018

Stochastic vs. sensitivity-based integral parameter and nuclear data adjustments

Andreas Pautz, Mathieu Hursin, Dimitri Rochman, Daniel Jerôme Siefman

Developments in data assimilation theory allow to adjust integral parameters and cross sections with stochastic sampling. This work investigates how two stochastic methods, MOCABA and BMC, perform relative to a sensitivity-based methodology called GLLS. St ...

SPRINGER HEIDELBERG2018

Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models

Sylvain Calinon, Ajay Kumar Tanwani, Swati Krishnan

Generalizing manipulation skills to new situations requires extracting invariant patterns from demonstrations. For example, the robot needs to understand the demonstrations at a higher level while being invariant to the appearance of the objects, geometric ...

2018

Chaining Mutual Information and Tightening Generalization Bounds

Emmanuel Abbé

Bounding the generalization error of learning algorithms has a long history, which yet falls short in explaining various generalization successes including those of deep learning. Two important difficulties are (i) exploiting the dependencies between the h ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018

Impact of Sample Sizes on Information Theoretic Measures for Audio-Visual Signal Processing

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Mutual Information for the Stochastic Block Model by the Adaptive Interpolation Method

Recovering covariance from functional fragments

Robust T2 Relaxometry with Hamiltonian MCMC for Myelin Water Fraction Estimation

Database Alignment with Gaussian Features

Quantifying high-order interdependencies via multivariate extensions of the mutual information

The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

Semiparametric Bayesian Risk Estimation for Complex Extremes

Stochastic vs. sensitivity-based integral parameter and nuclear data adjustments

Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models

Chaining Mutual Information and Tightening Generalization Bounds

Robust T2 Relaxometry with Hamiltonian MCMC for Myelin Water Fraction Estimation

Recovering covariance from functional fragments

Mutual Information for the Stochastic Block Model by the Adaptive Interpolation Method

Chaining Mutual Information and Tightening Generalization Bounds

Quantifying high-order interdependencies via multivariate extensions of the mutual information

Database Alignment with Gaussian Features

The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

Semiparametric Bayesian Risk Estimation for Complex Extremes

Stochastic vs. sensitivity-based integral parameter and nuclear data adjustments

Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models