Publications related to In Situ Calibration of Low-cost Air Quality Sensors using Artificial Neural Network

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Herein, machine learning (ML) models using multiple linear regression (MLR), support vector regression (SVR), random forest (RF) and artificial neural network (ANN) are developed and compared to predict the output features viz. specific capacitance (Csp), ...

Lausanne2024

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

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Stable parameterization of continuous and piecewise-linear functions

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Rectified-linear-unit (ReLU) neural networks, which play a prominent role in deep learning, generate continuous and piecewise-linear (CPWL) functions. While they provide a powerful parametric representation, the mapping between the parameter and function s ...

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A new variable shape parameter strategy for RBF approximation using neural networks

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The choice of the shape parameter highly effects the behaviour of radial basis function (RBF) approximations, as it needs to be selected to balance between the ill-conditioning of the interpolation matrix and high accuracy. In this paper, we demonstrate ho ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Bayes-optimal Learning of Deep Random Networks of Extensive-width

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We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

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Adequacy of stationary measurements as proxies for residential personal exposure to gaseous and particle air pollutants

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People are exposed to myriad of airborne pollutants in their homes. Owing to diverse potential sources of air pollution and human activity patterns, accurate assessment of residential exposures is complex. In this study, we explored the relationship betwee ...

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Hands-on reservoir computing: a tutorial for practical implementation

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This manuscript serves a specific purpose: to give readers from fields such as material science, chemistry, or electronics an overview of implementing a reservoir computing (RC) experiment with her/his material system. Introductory literature on the topic ...

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Exploring quantum perceptron and quantum neural network structures with a teacher-student scheme

Near-term quantum devices can be used to build quantum machine learning models, such as quantum kernel methods and quantum neural networks (QNN), to perform classification tasks. There have been many proposals on how to use variational quantum circuits as ...

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Adaptive hot water production based on Supervised Learning

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A major challenge in the common approach of hot water generation in residential houses lies in the highly stochastic nature of domestic hot water (DHW) demand. Learning hot water use behavior enables water heating systems to continuously adapt to the stoch ...

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Mixed-Precision Deep Learning Based on Computational Memory

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Deep neural networks (DNNs) have revolutionized the field of artificial intelligence and have achieved unprecedented success in cognitive tasks such as image and speech recognition. Training of large DNNs, however, is computationally intensive and this has ...

FRONTIERS MEDIA SA2020

In Situ Calibration of Low-cost Air Quality Sensors using Artificial Neural Network

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Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Stable parameterization of continuous and piecewise-linear functions

A new variable shape parameter strategy for RBF approximation using neural networks

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Adequacy of stationary measurements as proxies for residential personal exposure to gaseous and particle air pollutants

Hands-on reservoir computing: a tutorial for practical implementation

Exploring quantum perceptron and quantum neural network structures with a teacher-student scheme

Adaptive hot water production based on Supervised Learning

Mixed-Precision Deep Learning Based on Computational Memory

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Exploring quantum perceptron and quantum neural network structures with a teacher-student scheme

Adaptive hot water production based on Supervised Learning

Mixed-Precision Deep Learning Based on Computational Memory

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Stable parameterization of continuous and piecewise-linear functions

A new variable shape parameter strategy for RBF approximation using neural networks

Hands-on reservoir computing: a tutorial for practical implementation

Adequacy of stationary measurements as proxies for residential personal exposure to gaseous and particle air pollutants