Probabilistic Model Falsification for Infrastructure Diagnosis

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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 ...

Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

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Whereas the ability of deep networks to produce useful predictions on many kinds of data has been amply demonstrated, estimating the reliability of these predictions remains challenging. Sampling approaches such as MC-Dropout and Deep Ensembles have emerge ...

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

Recently, there has been an arms race of pose forecasting methods aimed at solving the spatio-temporal task of predicting a sequence of future 3D poses of a person given a sequence of past observed ones. However, the lack of unified benchmarks and limited ...

How to measure students' Computational Problem-Solving (CPS) competencies is an ongoing research topic. Prevalent approaches vary by measurement tools (e.g., interactive programming, multiple-choice tests, or programming-independent tests) and task types ( ...

We prove global in time well-posedness for perturbations of the 2D stochastic Navier-Stokes equations partial derivative( t)u + u center dot del u = Delta u - del p + sigma + xi, u(0, center dot ) = u(0),div (u) = 0, driven by additive space-time white noi ...

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There is a bias in the inference pipeline of most diffusion models. This bias arises from a signal leak whose distribution deviates from the noise distribution, creating a discrepancy between training and inference processes. We demonstrate that this signa ...

Static and mobile sensor nodes can be employed in gas monitoring tasks to detect gas leaks in an early stage and localize gas sources. Due to the intermittent nature of gas plumes and the slow dynamics of commonly used gas sensors, measuring gas concentrat ...

High-level waste, stemming from nuclear electricity generation poses significant environmental and safety concerns. Currently, high-level wastes are stored in interim facilities needing constant monitoring and waiting for a definitive solution. Deep geolog ...

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This thesis links two realms of particle accelerator dynamics and precision particle physics. The achievement of precise luminosity measurement at hadron colliders is enabled with dedicated luminometers. For the Run 3 period, the luminometer upgrade was ...

Most codes of practice adopt a semi probabilistic design approach for the dimensioning and assessment of structures. Accordingly, structural safety is ensured by performing limit state verifications using design values determined with adequately calibrated ...

Probabilistic Model Falsification for Infrastructure Diagnosis

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

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Spectral Estimators for High-Dimensional Matrix Inference

Design of an Open-Loop Pile-Oscillation Program in the CROCUS Reactor

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Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Toward Reliable Human Pose Forecasting With Uncertainty

A Comparative Analysis of Tools & Task Types for Measuring Computational Problem-Solving

Global existence for perturbations of the 2D stochastic Navier-Stokes equations with space-time white noise

Luminosity determination using Z boson production at the CMS experiment

Model uncertainties in action effects and load bearing capacity calculation in statically indeterminate reinforced concrete structures

Graph generative deep learning models with an application to circuit topologies

Exploiting the Signal-Leak Bias in Diffusion Models

Design and Evaluation of Modular Gas and Wind Sensing Nodes for Static and Mobile Deployments

A FEM modelling workflow to simulate THM effects in the rock around nuclear waste packages

Quantum Protocols for ML, Physics, and Finance

Dual-frame optimization for informationally complete quantum measurements

Precision luminosity measurement at hadron colliders

Influence of model uncertainty and long term deformations in action effects calculation in reinforced concrete structures