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The "Liquid Computer": A Novel Strategy for Real-Time Computing on Time Series

Publications associées (46)

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Spiking neural networks (SNN) are computational models inspired by the brain's ability to naturally encode and process information in the time domain. The added temporal dimension is believed to render them more computationally efficient than the conventio ...

2020

Analytic performance modeling and analysis of detailed neuron simulations

Francesco Cremonesi, Gerhard Wellein

Big science initiatives are trying to reconstruct and model the brain by attempting to simulate brain tissue at larger scales and with increasingly more biological detail than previously thought possible. The exponential growth of parallel computer perform ...

2020

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Being able to replicate real experiments with computational simulations is a unique opportunity to refine and validate models with experimental data and redesign the experiments based on simulations. However, since it is technically demanding to model all ...

FRONTIERS MEDIA SA2020

Intense x-ray free-electron laser (XFEL) pulses hold great promise for imaging function in nanoscale and biological systems with atomic resolution. So far, however, the spatial resolution obtained from single shot experiments lags averaging static experime ...

2020

Facile One-Pot Assembly of Push-Pull Imines by a Selective C-F Substitution Process in Aryl Fluorides

Shubhajit Das

Herein, we report the synthesis of a series of push-pull imines by considering cyclic diamino substituent at the C-centre and fluoroaryl substituent at the N-centre. This has been achieved by a selective aromatic nucleophilic substitution of different fluo ...

WILEY-V C H VERLAG GMBH2020

Computational methods are crucial for the analysis of diffusion magnetic resonance imaging (MRI) of the brain. Computational diffusion MRI can provide rich information at many size scales, including local microstructure measures such as diffusion anisotrop ...

2019

Computational intelligence methods for the fatigue life modeling of composite materials

Anastasios Vassilopoulos

Novel computational methods such as artificial neural networks, adaptive neuro-fuzzy inference systems and genetic programming are used in this chapter for the modeling of the nonlinear behavior of composite laminates subjected to constant amplitude loadin ...

Elsevier2019

Code Generation in Computational Neuroscience: A Review of Tools and Techniques

Michael Lee Hines, Pramod Shivaji Kumbhar, Romain Brette

Advances in experimental techniques and computational power allowing researchers to gather anatomical and electrophysiological data at unprecedented levels of detail have fostered the development of increasingly complex models in computational neuroscience ...

2018

Reprogramming the B1 Domain of Streptococcal Protein G (GB1)

Esra Bozkurt

Nature has the ability to cope with extreme pH, temperature and pressure, in addition to bestowing a wide array of functionalities to (bio)macromolecules. These specialized skills have attracted the interest of vast scientific communities especially in vie ...

EPFL2018

Computational methods and modeling of cellular function for the optimization of protein production and the study of cellular disease states

Joana Raquel Pinto Vieira

Systems biology is a multidisciplinary field that weaves together all the basic sciences through the use of computational and bioinformatics tools, to provide a more integrative view of the complex molecular interactions taking place within and among cells ...

EPFL2017