#### Filter Results:

- Full text PDF available (18)

#### Publication Year

2004

2017

- This year (1)
- Last 5 years (16)
- Last 10 years (22)

#### Publication Type

#### Co-author

#### Journals and Conferences

#### Key Phrases

Learn More

- Romain Reuillon
- 2008

- Lydia Maigne, David R. C. Hill, +4 authors Denise Donnarieix
- Parallel Processing Letters
- 2004

Monte Carlo simulations are increasingly used in medical physics. In scintigraphic imaging these simulations are used to model imaging systems and to develop and assess tomographic reconstruction algorithms and correction methods for improved image quantization. In radiotherapy-brachytherapy the goal is to evaluate accurately the dosimetry in complex… (More)

- Romain Reuillon, Florent Chuffart, Mathieu Leclaire, Thierry Faure, Nicolas Dumoulin, David R. C. Hill
- 2010 International Conference on High Performance…
- 2010

In this paper we present OpenMOLE, a scientific framework providing a virtualized runtime environment for distributed computing. Current distributed execution systems do not hide the hardware and software heterogeneity of computing and data resources whereas OpenMOLE provides generic services to develop distributed scientific algorithms independently from… (More)

- Romain Reuillon, Mathieu Leclaire, Sebastien Rey-Coyrehourcq
- Future Generation Comp. Syst.
- 2013

Complex-systems describe multiple levels of collective structure and organization. In such systems, the emergence of global behaviour from local interactions is generally studied through large scale experiments on numerical models. This analysis generates important computation loads which require the use of multi-core servers, clusters or grid computing.… (More)

- Romain Reuillon, Mamadou Kaba Traoré, Jonathan Passerat-Palmbach, David R. C. Hill
- Concurrency and Computation: Practice and…
- 2012

Bayesian networks are stochastic models, widely adopted to encode knowledge in several fields. One of the most interesting features of a Bayesian network is the possibility of learning its structure from a set of data, and subsequently use the resulting model to perform new predictions. Structure learning for such models is a NP-hard problem, for which the… (More)

Multi-agent geographical models integrate very large numbers of spatial interactions. In order to validate those models large amount of computing is necessary for their simulation and calibration. Here a new data processing chain including an automated calibration procedure is experimented on a computational grid using evolutionary algorithms. This is… (More)

- Guillaume Chérel, Clémentine Cottineau, Romain Reuillon, Frédéric Amblard
- PloS one
- 2015

Models of emergent phenomena are designed to provide an explanation to global-scale phenomena from local-scale processes. Model validation is commonly done by verifying that the model is able to reproduce the patterns to be explained. We argue that robust validation must not only be based on corroboration, but also on attempting to falsify the model, i.e.… (More)

- Romain Reuillon, Clara Schmitt, Ricardo de Aldama, Jean-Baptiste Mouret
- J. Artificial Societies and Social Simulation
- 2015

- Jean-Baptiste Rouquier, Isabelle Alvarez, Romain Reuillon, Pierre-Henri Wuillemin
- Annals of Mathematics and Artificial Intelligence
- 2015

In the framework of Decision Support Systems, mathematical viability theory can be used to classify the states and the trajectories of a dynamical system evolving in a set of desirable states. Since obtaining this viability theory output is a complex and computationally intensive task, we propose in this article to consider a compact representation of this… (More)