Concept
Nonprobability sampling
Related publications (386)
ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference
Nikita Durasov, Minh Hieu Lê, Nik Joel Dorndorf
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 ...
2024Gibbs sampling the posterior of neural networks
Lenka Zdeborová, Giovanni Piccioli, Emanuele Troiani
In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation in the network, arguing that the resulting posterior can be sampled using an ...
Bristol2024DiffAirfoil: An Efficient Novel Airfoil Sampler Based on Latent Space Diffusion Model for Aerodynamic Shape Optimization
Surrogate-based optimization is widely used for aerodynamic shape optimization, and its effectiveness depends on representative sampling of the design space. However, traditional sampling methods are hard-pressed to effectively sample high-dimensional desi ...
2024Identification of typical district configurations: A two-step global sensitivity analysis framework
François Maréchal, Jonas Schnidrig, Cédric Terrier
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 Ltd2024Influence of Si3N4 fillers and pyrolysis profile on the microstructure of additively manufactured silicon carbonitride ceramics derived from polyvinylsilazane
In this work, various methods were used to improve the printability of a photocurable polyvinylsilazane resin filled with silicon nitride particles for digital light processing. The developed resin was used as a preceramic polymer for polymer-to-ceramic co ...
Taylor & Francis Ltd2024Reducing Annotation Efforts in Electricity Theft Detection Through Optimal Sample Selection
Supervised machine learning models are receiving increasing attention in electricity theft detection due to their high detection accuracy. However, their performance depends on a massive amount of labeled training data, which comes from time-consuming and ...
Piscataway2024Thermal transport of glasses via machine learning driven simulations
Accessing the thermal transport properties of glasses is a major issue for the design of production strategies of glass industry, as well as for the plethora of applications and devices where glasses are employed. From the computational standpoint, the che ...
Lausanne2024An immersive virtual reality tool for assessing left and right unilateral spatial neglect
Olaf Blanke, Andrea Serino, Roberta Ronchi
The reported rate of the occurrence of unilateral spatial neglect (USN) is highly variable likely due to the lack of validity and low sensitivity of classical tools used to assess it. Virtual reality (VR) assessments try to overcome these limitations by pr ...
Hoboken2024A state-of-the-art, systematic review of indoor environmental quality studies in work-from-home settings
The COVID-19 pandemic has led to a significant increase in working from home worldwide, making the workfrom-home (WFH) setting a crucial context for studying the influence of indoor environmental quality (IEQ) on workers' well-being and productivity. A nar ...
Pergamon-Elsevier Science Ltd2024Into the ice: Exploration and data capturing in glacial moulins by a tethered robot
Josephine Anna Eleanor Hughes, Max Mirko Polzin
Glacial moulins (cylindrical meltwater drainage shafts) provide valuable insights into glacier dynamics, but are inaccessible and hazardous environments for humans to study. Exploring them using passive sensor probes has revealed their complex geometry, wh ...
Hoboken2024