Publications associées à Non-uniform random variate generation

Secondary structure of the human mitochondrial genome affects formation of deletions

BackgroundAging in postmitotic tissues is associated with clonal expansion of somatic mitochondrial deletions, the origin of which is not well understood. Such deletions are often flanked by direct nucleotide repeats, but this alone does not fully explain ...

BMC2023

Chaotic microcomb-based parallel ranging

Tobias Kippenberg, Aleksandr Tusnin, Junqiu Liu, Anton Lukashchuk

The intrinsic random amplitude and phase modulation of 40 distinct lines of a microresonator frequency comb operated in the modulation instability regime are used to realize massively parallel random-modulation continuous-wave light detection and ranging, ...

Nature Publishing Group2023

Stop Wasting my FLOPS: Improving the Efficiency of Deep Learning Models

Angelos Katharopoulos

Deep neural networks have completely revolutionized the field of machine learning by achieving state-of-the-art results on various tasks ranging from computer vision to protein folding. However, their application is hindered by their large computational an ...

EPFL2022

Distributionally Robust Optimization with Markovian Data

Daniel Kuhn, Tobias Sutter, Mengmeng Li

We study a stochastic program where the probability distribution of the uncertain problem parameters is unknown and only indirectly observed via finitely many correlated samples generated by an unknown Markov chain with d states. We propose a data-driven d ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

Iron incorporation in synthetic precipitated calcium silicate hydrates

David Lyndon Emsley, Paul Bowen, Brennan James Walder, Jirawan Siramanont

Effect of Fe3+ on the precipitation of synthetic calcium silicate hydrates (C-S-H) under controlled conditions has been evaluated. Using extremely basic either initial calcium nitrate or sodium silicate solutions (pH > 11), incipient formation of ferrihydr ...

Pergamon-Elsevier Science Ltd2021

Uncertain Sampling with Certain Priors

Golnooshsadat Elhami

Sampling has always been at the heart of signal processing providing a bridge between the analogue world and discrete representations of it, as our ability to process data in continuous space is quite limited. Furthermore, sampling plays a key part in unde ...

EPFL2021

Large-Eddy Simulation of Wind Turbine Flows: A New Evaluation of Actuator Disk Models

Fernando Porté Agel, Tristan Revaz

Large-eddy simulation (LES) with actuator models has become the state-of-the-art numerical tool to study the complex interaction between the atmospheric boundary layer (ABL) and wind turbines. In this paper, a new evaluation of actuator disk models (ADMs) ...

2021

CPGD: Cadzow Plug-and-Play Gradient Descent for Generalised FRI

Martin Vetterli, Paul Hurley, Matthieu Martin Jean-André Simeoni, Adrien Georges Jean Besson

Finite rate of innovation (FRI) is a powerful reconstruction framework enabling the recovery of sparse Dirac streams from uniform low-pass filtered samples. An extension of this framework, called generalised FRI (genFRI), has been recently proposed for han ...

2020

Uncertainty propagation based on correlated sampling technique for nuclear data applications

Andreas Pautz, Vincent Pierre Lamirand, Axel Guy Marie Laureau, Dimitri Rochman

A correlated sampling technique has been implemented to estimate the impact of cross section modifications on the neutron transport and in Monte Carlo simulations in one single calculation. This implementation has been coupled to a Total Monte Carlo approa ...

2020

Variance-Reduced Stochastic Learning Under Random Reshuffling

Ali H. Sayed, Bicheng Ying, Kun Yuan

Several useful variance-reduced stochastic gradient algorithms, such as SVRG, SAGA, Finito, and SAG, have been proposed to minimize empirical risks with linear convergence properties to the exact minimizer. The existing convergence results assume uniform d ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Max-infinitely divisible models and inference for spatial extremes

Emeric Rolland Georges Thibaud, Raphaël Huser

For many environmental processes, recent studies have shown that the dependence strength is decreasing when quantile levels increase. This implies that the popular max-stable models are inadequate to capture the rate of joint tail decay, and to estimate jo ...

WILEY2021

Multithermal-Multibaric Molecular Simulations from a Variational Principle

Pablo Miguel Piaggi, Michele Parrinello

We present a method for performing multithermal-multibaric molecular dynamics simulations that sample entire regions of the temperature-pressure (TP) phase diagram. The method uses a variational principle [Valsson and Parrinello, Phys. Rev. Lett. 113, 0906 ...

2019

Influence of curved delamination front on R-curve of DCB specimen

Thomas Keller, Anastasios Vassilopoulos, Zhengwen Jiang

This work investigated the evolution of the non-uniform distribution of Mode-I strain energy release rate (SERR) along a straight pre-crack front of double cantilever beams (DCB), caused by the anticlastic deformation and the longitudinal free-edge effects ...

ELSEVIER SCI LTD2019

Subjective and physiological responses to façade and sunlight pattern geometry in virtual reality

Marilyne Andersen, Jan Wienold, Giorgia Chinazzo, Kynthia Chamilothori, João Pedro de Matos Rodrigues

This study investigates the joint impact of façade geometry and associated sunlight patterns on occupant subjective perception and physiological responses through a novel experimental method coupling physically-based simulations shown in virtual reality wi ...

2019

Millimeter-Wave Heating in In Vitro Studies: Effect of Convection in Continuous and Pulse-Modulated Regimes

Denys Nikolayev

Shallow penetration of millimeter waves (MMW) and non-uniform illumination in in vitro experiments result in a non-uniform distribution of the specific absorption rate (SAR). These SAR gradients trigger convective currents in liquids affecting transient an ...

WILEY2019

Time- and Space-Efficient Spatial Data Analytics

Mirjana Pavlovic

Advances in data acquisition technologies and supercomputing for large-scale simulations have led to an exponential growth in the volume of spatial data. This growth is accompanied by an increase in data complexity, such as spatial density, but also by mor ...

EPFL2019

Unified Theory for Recovery of Sparse Signals in a General Transform Domain

Kyong Hwan Jin

Compressed sensing is provided a data-acquisition paradigm for sparse signals. Remarkably, it has been shown that the practical algorithms provide robust recovery from noisy linear measurements acquired at a near optimal sampling rate. In many real-world a ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Maturing Mycobacterium smegmatis peptidoglycan requires non-canonical crosslinks to maintain shape

Georg Fantner, John McKinney, Haig Alexander Eskandarian

In most well-studied rod-shaped bacteria, peptidoglycan is primarily crosslinked by penicillin-binding proteins (PBPs). However, in mycobacteria, crosslinks formed by L,D-transpeptidases (LDTs) are highly abundant. To elucidate the role of these unusual cr ...

ELIFE SCIENCES PUBLICATIONS LTD2018

Sampling at unknown locations: Uniqueness and reconstruction under constraints

Martin Vetterli, Benjamin Bejar Haro, Adam James Scholefield, Golnooshsadat Elhami, Michalina Wanda Pacholska

Traditional sampling results assume that the sample locations are known. Motivated by simultaneous localization and mapping (SLAM) and structure from motion (SfM), we investigate sampling at unknown locations. Without further constraints, the problem is of ...

2018

Learning without Smoothness and Strong Convexity

Yen-Huan Li

Recent advances in statistical learning and convex optimization have inspired many successful practices. Standard theories assume smoothness---bounded gradient, Hessian, etc.--- and strong convexity of the loss function. Unfortunately, such conditions may ...

EPFL2018