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In response to ‘Six critical questions about smart spezialisation’

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The input of almost every machine learning algorithm targeting the properties of matter at the atomic scale involves a transformation of the list of Cartesian atomic coordinates into a more symmetric representation. Many of the most popular representations ...

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The COUGHVID crowdsourcing dataset: A corpus for the study of large-scale cough analysis algorithms

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Overview Cough audio signal classification has been successfully used to diagnose a variety of respiratory conditions, and there has been significant interest in leveraging Machine Learning (ML) to provide widespread COVID-19 screening. Th ...

Zenodo2021

Deep learning architectures for estimating breathing signal and respiratory parameters from speech recordings

Mathew Magimai Doss, Zohreh Mostaani, Venkata Srikanth Nallanthighal

Respiration is an essential and primary mechanism for speech production. We first inhale and then produce speech while exhaling. When we run out of breath, we stop speaking and inhale. Though this process is involuntary, speech production involves a system ...

PERGAMON-ELSEVIER SCIENCE LTD2021

Predictive brain: Addressing the level of representation by reviewing perceptual hysteresis

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In recent years, the idea that the prediction of sensory input is one of the major computational goals of the nervous system led to the development of several large-scale theories of brain functioning, such as different versions of the Bayesian approach to ...

ELSEVIER MASSON, CORP OFF2021

Standard model meets gravity: Electroweak symmetry breaking and inflation

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We propose a model for combining the Standard Model (SM) with gravity. It relies on a nonminimal coupling of the Higgs field to the Ricci scalar and on the Palatini formulation of gravity. Without introducing any new degrees of freedom in addition to those ...

American Physical Society2021

The Cost of Scaling a Reliable Interconnection Topology

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In distributed computing, many papers try to evaluate the message complexity of a distributed system as a function of the number of nodes n. But what about the cost of building the distributed system itself? Assuming that we want to reliably connect n node ...

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Private and Secure Distributed Learning

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The ever-growing number of edge devices (e.g., smartphones) and the exploding volume of sensitive data they produce, call for distributed machine learning techniques that are privacy-preserving. Given the increasing computing capabilities of modern edge de ...

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Six additional replies - one more chorus of the S3 ballad

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This paper has been written as a response to 'Six additional questions about smart specialization: implications for regional innovation policy 4.0' by M. Benner. The paper starts with the argument that recent academic work has enabled considerable progress ...

ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD2020

Reduction of the sign problem near T=0 in quantum Monte Carlo simulations

Frédéric Mila, Jonathan D'Emidio

Building on a recent investigation of the Shastry-Sutherland model [S. Wessel et al., Phys. Rev. B 98, 174432 (2018)], we develop a general strategy to eliminate the Monte Carlo sign problem near the zero-temperature limit in frustrated quantum spin models ...

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International Perspective on UHPC in Bridge Engineering

Eugen Brühwiler

Ultrahigh-performance concrete (UHPC) offers significant potential to address a variety of needs in bridge design, construction, and performance enhancement. Bridge owners have shown willingness to embrace novel solutions that could address specific challe ...

ASCE-AMER SOC CIVIL ENGINEERS2020