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Related publications (21)

Page 1 of 2

Teaching about non-deterministic physics: an almost forgotten fundamental contribution of Marie Curie

Giorgio Margaritondo

The first historical steps of radioactivity research offer an excellent opportunity to teach a key concept of modern physics: non-deterministic phenomena. However, this opportunity is often wasted because of historical misconceptions and of the irrational ...

Iop Publishing Ltd2024

Taming neuronal noise with large networks

Valentin Marc Schmutz

How does reliable computation emerge from networks of noisy neurons? While individual neurons are intrinsically noisy, the collective dynamics of populations of neurons taken as a whole can be almost deterministic, supporting the hypothesis that, in the br ...

EPFL2022

Nonlinear reconstruction of bioclimatic outdoor-environment dynamics for the Lower Silesia region (SW Poland)

Paolo Perona

Measured meteorological time series are frequently used to obtain information 8 about climate dynamics. We use time series analysis and nonlinear system identification 9 methods in order to assess outdoor-environment bioclimatic conditions starting from th ...

2021

Feedback Control Design Maximizing the Region of Attraction of Stochastic Systems Using Polynomial Chaos Expansion

Petr Listov

A feedback control design is proposed for stochastic systems with finite second moment which aims at maximising the region of attraction of the equilibrium point. Polynomial Chaos (PC) expansions are employed to represent the stochastic closed loop system ...

ELSEVIER2020

On the relaxed maximum-likelihood blind MIMO channel estimation for orthogonal space-time block codes

Kamran Kalbasi

This paper concerns the maximum-likelihood channel estimation for MIMO systems with orthogonal space-time block codes when the finite alphabet constraint of the signal constellation is relaxed. We study the channel coefficients estimation subspace generate ...

ELSEVIER2020

Invariant solutions underlying small- and large-scale structures in turbulent boundary layers

Sajjad Azimi

Flows of gases and liquids interacting with solid objects are often turbulent within a thin boundary layer. As energy dissipation and momentum transfer are dominated by the boundary layer dynamics, many engineering applications can benefit from an improved ...

EPFL2020

A solution method for predictive simulations in a stochastic environment

Anne Daniëlle Koelewijn

Predictive gait simulations currently do not account for environmental or internal noise. We describe a method to solve predictive simulations of human movements in a stochastic environment using a collocation method. The optimization is performed over mul ...

2020

The dynamics of motor learning through the formation of internal models

Camilla Pierella

A medical student learning to perform a laparoscopic procedure or a recently paralyzed user of a powered wheelchair must learn to operate machinery via interfaces that translate their actions into commands for an external device. Since the user’s actions a ...

2019

New Approach to Identifying Critical Initial Conditions for Extreme Flood Simulations in a Semicontinuous Simulation Framework

Anton Schleiss, Bettina Schaefli, Javier García Hernández, Fränz Zeimetz, Guillaume Mathieu Artigue

Extreme flood simulation with synthetic extreme precipitation events raises unavoidable questions about the choice of initial conditions. State-of-the-art extreme flood estimation frameworks propose to address these questions with the help of semicontinuou ...

2018

Deterministic Algorithms for Submodular Maximization Problems

Moran Feldman

Randomization is a fundamental tool used in many theoretical and practical areas of computer science. We study here the role of randomization in the area of submodular function maximization. In this area, most algorithms are randomized, and in almost all c ...

ASSOC COMPUTING MACHINERY2018

Deriving a load model for the braking force on road bridges: Comparison between a deterministic and a probabilistic approach

Katrin Beyer, André-Gilles Dumont, Marc-Antoine Fénart

The current provisions for the braking force in the Eurocodes are much more demanding than previously enforced national codes from most European countries. Hence, safety assessments of existing bridges may show a lack of compliance with the new safety requ ...

Springer International Publishing2016

Error Analysis of the Dynamically Orthogonal Approximation of Time Dependent Random PDEs

Fabio Nobile, Eleonora Musharbash

In this work we discuss the dynamically orthogonal (DO) approximation of time dependent partial differential equations with random data. The approximate solution is expanded at each time instant on a time dependent orthonormal basis in the physical domain ...

2015

Randomized versus Deterministic Implementations of Concurrent Data Structures

Dan Alistarh

One of the key trends in computing over the past two decades has been increased distribution, both at the processor level, where multi-core architectures are now the norm, and at the system level, where many key services are currently distributed overmulti ...

EPFL2012

The Complexity of Renaming

Rachid Guerraoui, Seth Gilbert, Dan Alistarh

We study the complexity of renaming, a fundamental problem in distributed computing in which a set of processes need to pick distinct names from a given namespace. We prove an individual lower bound of Omega(k) process steps for deterministic renaming into ...

Ieee Computer Soc Press, Customer Service Center, Po Box 3014, 10662 Los Vaqueros Circle, Los Alamitos, Ca 90720-1264 Usa2011

Compressibility of Deterministic and Random Infinite Sequences

Michaël Unser, Arash Amini

We introduce a definition of the notion of compressibility for infinite deterministic and i.i.d. random sequences which is based on the asymptotic behavior of truncated subsequences. For this purpose, we use asymptotic results regarding the distribution of ...

IEEE2011

Constrained expectation-maximization algorithm for stochastic inertial error modeling: study of feasibility

Jan Skaloud, Stéphane Guerrier, Yannick Stebler

Stochastic modeling is a challenging task for low-cost sensors whose errors can have complex spectral structures. This makes the tuning process of the INS/GNSS Kalman filter often sensitive and difficult. For example, first-order Gauss–Markov processes are ...

IOP Publishing2011

Firing patterns in the adaptive exponential integrate-and-fire model

Wulfram Gerstner, Richard Naud, Nicolas Marcille

For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-equation model: the adaptive exponential integrate-and-fire neuron. We show th ...

Springer Verlag2008

Singularly perturbed piecewise deterministic games

In this paper we consider a class of hybrid stochastic games with the piecewise open-loop information structure. These games are indexed over a parameter

\varepsilon

which represents the time scale ratio between the stochastic (jump process) and the dete ...

Society for Industrial and Applied Mathematics2008

A Class Of Mean Field Interaction Models for Computer and Communication Systems

Jean-Yves Le Boudec

We consider models of N interacting objects, where the interaction is via a common resource and the distribution of states of all objects. We introduce the key scaling concept of intensity; informally, the expected number of transitions per object per time ...

2008

Distributed Coverage: From Deterministic to Probabilistic Models

Alcherio Martinoli, Nicolaus Correll

For the multi-robot coverage problem determin- istic deliberative as well as probabilistic approaches have been proposed. Whereas deterministic approaches usually provide provable completeness and promise good performance under perfect conditions, probabil ...

2007