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