Three essays on access to knowledge

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In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

In acute ischemic stroke, the composition of the occlusive clot can be associated with the underlying pathophysiology and the response to treatment. For these reasons, it is important to characterize the clot composition from clinical scans. We examine the ...

We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo theory of linear response and Bayesian regression analysis. By exploiting the ...

The optimal pricing of goods, especially when they are new and the innovating firm is a monopolist, must proceed without precise knowledge of the demand curve. This paper provides a pricing method with a relative robustness guarantee by maximizing a perfor ...

We consider on the torus the scaling limit of stochastic 2D (inviscid) fluid dynamics equations with transport noise to deterministic viscous equations. Quantitative estimates on the convergence rates are provided by combining analytic and probabilistic ar ...

Crop maps are crucial for agricultural monitoring and food management and can additionally support domain-specific applications, such as setting cold supply chain infrastructure in developing countries. Machine learning (ML) models, combined with freely-av ...

Correlated errors of experimental data are a common but often neglected problem in physical sciences. Various tools are provided here for thorough propagation of uncertainties in cases of correlated errors. Discussed are techniques especially applicable to ...

Automatic verification of programs manipulating arrays relies on specialised decision procedures. A methodology to classify the theories handled by these procedures is introduced. It is based on decomposition theorems in the style of Feferman and Vaught. T ...

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 ...

Modern data-driven science often consists of iterative cycles of data discovery, acquisition, preparation, analysis, model building and validation leading to knowledge discovery as well as dissemination at scale. The unique challenges of building and simul ...

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 ...

Professionals in the building design and operation fields typically look at standards and guidelines as a reliable source of information and guidance with regard to procedural, contractual, and legal scope and requirements that are relevant to accountabili ...

The establishment of company towns played a significant role in developing both urban and rural areas in Europe during the nineteenth and twentieth centuries. By combining historical and urban research, this study provides findings about the industry's pol ...

This thesis studies the origins and consequences of financial crises, and computational techniques to solve continuous-time economic models that explain such crises. The first chapter shows that financial recessions are typically characterised by a large ...

This perspective paper explores the rising impacts of the COVID-19 and the Russia-Ukraine war from different perspectives, with an emphasis on the role of climate financing in achieving equitable and just transition mechanisms and that of peace in expediti ...

We introduce HP, an implementation of density-functional perturbation theory, designed to compute Hubbard parameters (on-site U and inter-site V ) in the framework of DFT+U and DFT+U+V. The code does not require the use of computationally expensive superce ...

BackgroundTinnitus is a heterogeneous condition which may be associated with moderate to severe disability, but the reasons why only a subset of individuals is burdened by the condition are not fully clear. Ecological momentary assessment (EMA) allows a be ...

Unlike water and sanitation infrastructures or socio-economic indicators, landscape features are seldomly considered as predictors of diarrhoea. In contexts of rapid urbanisation and changes in the physical environment, urban planners and public health man ...

With the emergence of social networks and improvements in the internet speed, the video data has become an ever-increasing portion of the global internet traffic. Besides the content, the quality of a video sequence is an important issue at the user end wh ...

SwissCovid is the Swiss digital contact tracing app, which was deployed to help fighting against the COVID-19 pandemic. After a year of activity, it is high time to evaluate how effective it has been in its mission. At the highest peak, about 22% of the Sw ...

Three essays on access to knowledge

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Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

MRI characterization of in vitro clots at 3T and 7T: A technical note

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

Monopoly Pricing with Unknown Demand

Quantitative convergence rates for scaling limit of SPDEs with transport noise

Using machine learning to generate an open-access cropland map from satellite images time series in the Indian Himalayan region

Reliable uncertainties: Error correlation, rotated error bars, and linear regressions in three-isotope plots and beyond

On algebraic array theories

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

Blue Brain Nexus: An open, secure, scalable system for knowledge graph management and data-driven science

Stable parameterization of continuous and piecewise-linear functions

Thermal Conditions in Indoor Environments: Exploring the Reasoning behind Standard-Based Recommendations

Dalmine: From Company Town to Hybridized Productive Habitat

Essays in macro-finance and deep learning

The Rising Impacts of the COVID-19 Pandemic and the Russia-Ukraine War: Energy Transition, Climate Justice, Global Inequality, and Supply Chain Disruption

HP - A code for the calculation of Hubbard parameters using density-functional perturbation theory

Daily Contributors of Tinnitus Loudness and Distress: An Ecological Momentary Assessment Study

Using Open-Access Data to Explore Relations between Urban Landscapes and Diarrhoeal Diseases in Côte d’Ivoire

Feature-based no-reference video quality assessment using Extra Trees

SwissCovid in the Perspective of Its Goals