Learning Finance with Games: An Empirical Study

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AimPlant senescence largely influences the global carbon cycle by regulating the growing season length. However, the driving mechanisms of plant senescence remain unclear, particularly the role of developmental factors. This study aims to investigate how e ...

Biomass resources can play an important role in the energy transition, being a dynamic feedstock that can be transformed either into solid, liquid or gaseous fuels. The biomass gasification is a versatile way to convert wastes into energy. In this work, th ...

Semi-supervised semantic segmentation methods leverage unlabeled data by pseudo-labeling them. Thus the success of these methods hinges on the reliability of the pseudo-labels. Existing methods mostly choose high-confidence pixels in an effort to avoid err ...

In this thesis we present three closed form approximation methods for portfolio valuation and risk management. The first chapter is titled ``Kernel methods for portfolio valuation and risk management'', and is a joint work with Damir Filipovi'c (SFI and ...

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 ...

Torque teno virus (TTV) is considered to be an ubiquitous member of the commensal human blood virome commonly reported in mixed genotype co-infections. This study investigates the genomic diversity of TTV in blood samples from 816 febrile Tanzanian childre ...

Context Long-term adherence to physical activity (PA) interventions is challenging. The Lifestyle-integrated Functional Exercise programmes were adapted Lifestyle-integrated Functional Exercise (aLiFE) to include more challenging activities and a behaviour ...

Distribution-on-distribution regression considers the problem of formulating and es-timating a regression relationship where both covariate and response are probability distributions. The optimal transport distributional regression model postulates that th ...

The application of machine learning to theoretical chemistry has made it possible to combine the accuracy of quantum chemical energetics with the thorough sampling of finite-temperature fluctuations. To reach this goal, a diverse set of methods has been pr ...

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 ...

When enough annotated training data is available, supervised deep-learning. algorithms excel at estimating human body pose and shape using a single camera. The effects of too little such data being available can be mitigated by using other information sour ...

In this second part of the development of a mechanistic kinetic model of the solar inactivation of E. coli enhanced with hydrogen peroxide, we evaluate the mechanisms based on photonic inactivation and integrate them into the kinetic model of the dark proc ...

We develop a novel 2D functional learning framework that employs a sparsity-promoting regularization based on second-order derivatives. Motivated by the nature of the regularizer, we restrict the search space to the span of piecewise-linear box splines shi ...

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

Many applications, e.g. in content recommendation, sports, or recruitment, leverage the comparisons of alternatives to score those alternatives. The classical Bradley-Terry model and its variants have been widely used to do so. The historical model conside ...

The present bi-partite work describes the development and validation of a mechanistic kinetic model of SODIS E. coli inactivation, enhanced with H2O2. In this first part, the mechanism of the baseline dark phenomena is modelled. A mechanistic model involvi ...

We consider the problem of defining and fitting models of autoregressive time series of probability distributions on a compact interval of Double-struck capital R. An order-1 autoregressive model in this context is to be understood as a Markov chain, where ...

One paramount challenge in multi-ion-sensing arises from ion interference that degrades the accuracy of sensor calibration. Machine learning models are here proposed to optimize such multivariate calibration. However, the acquisition of big experimental da ...

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 ...

The hydropower sector has recently raised the interest in pump as turbine (PaT) that can be a valid trade-off between capital cost and performance in micro-scale installations. Nevertheless, the modest efficiency of PaTs often restricts their exploitation. ...

Learning Finance with Games: An Empirical Study

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Growth Onset Rather Than Photosynthesis Strongly Regulates Autumn Senescence Termination Besides Climate Change

Comparison of regression techniques for generating surrogate models to predict the thermodynamic behavior of biomass gasification systems

Weighting Pseudo-labels via High-Activation Feature Index Similarity and Object Detection for Semi-supervised Segmentation

Closed form approximation methods for portfolio valuation and risk management

Hands-on reservoir computing: a tutorial for practical implementation

Genomic Diversity of Torque Teno Virus in Blood Samples from Febrile Paediatric Outpatients in Tanzania: A Descriptive Cohort Study

Impact of adherence to a lifestyle-integrated programme on physical function and behavioural complexity in young older adults at risk of functional decline: a multicentre RCT secondary analysis

Minimax rate for optimal transport regression between distributions

Local Kernel Regression and Neural Network Approaches to the Conformational Landscapes of Oligopeptides

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

Using Motion Cues to Supervise Single-Frame Body Pose and Shape Estimation in Low Data Regimes

Mechanistic modelling of solar disinfection (SODIS) kinetics of Escherichia coli, enhanced with H2O2 - Part 2: Shine on you, crazy peroxide

Learning of Continuous and Piecewise-Linear Functions With Hessian Total-Variation Regularization

Random matrix methods for high-dimensional machine learning models

Generalized Bradley-Terry Models for Score Estimation from Paired Comparisons

Mechanistic modelling of solar disinfection (SODIS) kinetics of Escherichia coli, enhanced with H2O2 - part 1: The dark side of peroxide

On distributional autoregression and iterated transportation

Multi-ion-sensing emulator and multivariate calibration optimization by machine learning models

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

Numerical investigation on the volute cutwater for pumps running in turbine mode