Concept

Markov chain Monte Carlo

Related publications (449)

Efficient Learning from Comparisons

Humans are comparison machines: comparing and choosing an item among a set of alternatives (such as objects or concepts) is arguably one of the most natural ways for us to express our preferences and opinions. In many applications, the analysis of data con ...

EPFL2018

Application of a Point Estimate Method for incorporating the epistemic uncertainty in the seismic assessment of a masonry building

Katrin Beyer, Francesco Vanin

Several sources of uncertainty affect the assessment of existing buildings, including uncertainties associated with the material properties and the displacement capacity of the elements. In engineering practice, Monte Carlo simulations of the nonlinear sei ...

2018

Active contraction of cardiac cells: a reduced model for sarcomere dynamics with cooperative interactions

Alfio Quarteroni, Francesco Regazzoni

We propose a reduced ODE model for the mechanical activation of cardiac myofilaments, which is based on explicit spatial representation of nearest-neighbour interactions. Our model is derived from the cooperative Markov Chain model of Washio et al. (Cell M ...

SPRINGER HEIDELBERG2018

Enhancing Session-Based Recommendations through Sequential Modeling

Boi Faltings, Vincent Jean Fabrice Schickel, Stéphane Bernard Martin

Recommender systems typically determine the items they should recommend by learning models of user-preferences. Most often, those preferences are modeled as static and independent of context. In real life however, users consider items in sequence: TV serie ...

ASSOC COMPUTING MACHINERY2018

Enhancing Session-Based Recommendations through Sequential Modeling

Boi Faltings, Vincent Jean Fabrice Schickel, Stéphane Bernard Martin

ACM2018

MATHICSE Technical Report : Analysis of stochastic gradient methods for PDE-constrained optimal control problems with uncertain parameters

Fabio Nobile, Sebastian Krumscheid, Matthieu Claude Martin

We consider the numerical approximation of a risk-averse optimal control problem for an elliptic partial differential equation (PDE) with random coefficients. Specifically, the control function is a deterministic, dis- tributed forcing term that minimizes ...

MATHICSE2018

Gen-Oja: A Simple and Efficient Algorithm for Streaming Generalized Eigenvector Computation

Nicolas Henri Bernard Flammarion

In this paper, we study the problems of principal Generalized Eigenvector computation and Canonical Correlation Analysis in the stochastic setting. We propose a simple and efficient algorithm, Gen-Oja, for these problems. We prove the global convergence of ...

2018

Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo

Nisheeth Vishnoi, Oren Rami Mangoubi

Hamiltonian Monte Carlo (HMC) is a widely deployed method to sample from high-dimensional distributions in Statistics and Machine learning. HMC is known to run very efficiently in practice and its popular second-order "leapfrog" implementation has long bee ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018

Temperature Dependence of the Vacancy Formation Energy in Solid He-4

Riccardo Rota

We studied the thermal effects on the behavior of incommensurate solid He-4 at low temperatures using the path integral Monte Carlo method. Below a certain temperature, depending on the density and the structure of the crystal, the vacancies delocalize and ...

2018

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

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