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Electricity Load Forecasting for Residential Customers: Exploiting Aggregation and Correlation between Households

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During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and ...

Public Library Science2024

Machine Learning for Modeling Stock Returns

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Throughout history, the pace of knowledge and information sharing has evolved into an unthinkable speed and media. At the end of the XVII century, in Europe, the ideas that would shape the "Age of Enlightenment" were slowly being developed in coffeehouses, ...

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Network time series forecasting in photovoltaics power production

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Accurate forecasting of photovoltaic (PV) power production is crucial for the integration of more renewable energy sources into the power grid. PV power production is highly intermittent, due to the stochastic cloud behaviour and cloud dynamics. Previous w ...

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Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?

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Motion forecasting is crucial in enabling autonomous vehicles to anticipate the future trajectories of surrounding agents. To do so, it requires solving mapping, detection, tracking, and then forecasting problems, in a multi-step pipeline. In this complex ...

2024

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Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power. Simultaneously, a critical pain point arises as several computer vision applications are deploye ...

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Functional-Basis Analysis of Non-Stationary Signals in Modern Power Grids: Theory and Implementation in Embedded Systems

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Situational awareness strategies are essential for the reliable and secure operation of the electric power grid which represents critical infrastructure in modern society. With the rise of converter-interfaced renewable generation and the consequent shift ...

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Identification of typical district configurations: A two-step global sensitivity analysis framework

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The recent geopolitical conflicts in Europe have underscored the vulnerability of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy systems ensuring sustainable energy supply in the future, the ...

Pergamon-Elsevier Science Ltd2024

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

2

-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

EPFL2024

Maintenance and optimization of the TCV power supply

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The TCV tokamak is powered by a flywheel generator to supply the magnetic coils and the auxiliary heating systems. The generator has just undergone its fourth major overhaul to make it ready for the next ten years, after more than thirty years of almost tr ...

Elsevier Science Sa2024

Beyond the average consumer: Mapping the potential of demand-side management among patterns of appliance usage

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To support the decarbonisation of the power sector and offset the volatility of a system with high levels of renewables, there is growing interest in residential Demand-Side Management (DSM) solutions. Traditional DSM strategies require consumers to active ...

2024

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-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

EPFL2024

Maintenance and optimization of the TCV power supply

Damien Fasel, Ugo Siravo, Jérémie Dubray

Elsevier Science Sa2024

Beyond the average consumer: Mapping the potential of demand-side management among patterns of appliance usage

Claudia Rebeca Binder Signer, Matteo Barsanti, Selin Yilmaz

2024