Stochastic vs. sensitivity-based integral parameter and nuclear data adjustments

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We are interested in testing properties of distributions with systematically mislabeled samples. Our goal is to make decisions about unknown probability distributions, using a sample that has been collected by a confused collector, such as a machine-learni ...

Bioaerosols are emitted from various sources into the indoor environment and can positively and negatively impact human health. Humans are the major source of bioaerosol emissions indoors, specifically for bacteria. However, efficient sampling to guarantee ...

We present a new setup for resonant inelastic hard x-ray scattering at the Bernina beamline of SwissFEL with energy, momentum, and temporal resolution. The compact R = 0.5 m Johann-type spectrometer can be equipped with up to three crystal analyzers and al ...

We present Epidemic Learning ( EL ), a simple yet powerful decentralized learning (DL) algorithm that leverages changing communication topologies to achieve faster model convergence compared to conventional DL approaches. At each round of EL, each node sen ...

In this paper, we perform the joint study of scale -invariant operators and self -similar processes of complex order. More precisely, we introduce general families of scale -invariant complex -order fractional -derivation and integration operators by const ...

Deep-learning-based digital twins (DDT) are a promising tool for data-driven system health management because they can be trained directly on operational data. A major challenge for efficient training however is that industrial datasets remain unlabeled. T ...

This paper studies the infinite-width limit of deep linear neural networks (NNs) initialized with random parameters. We obtain that, when the number of parameters diverges, the training dynamics converge (in a precise sense) to the dynamics obtained from a ...

Domain generalization (DG) aims to learn a model from multiple training (i.e., source) domains that can generalize well to the unseen test (i.e., target) data coming from a different distribution. Single domain generalization (SingleDG) has recently emerge ...

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

We present an extended validation of semi-analytical, semi-empirical covariance matrices for the two-point correlation function (2PCF) on simulated catalogs representative of luminous red galaxies (LRGs) data collected during the initial 2 months of operat ...

We consider the problem of comparing several samples of stochastic processes with respect to their second-order structure, and describing the main modes of variation in this second order structure, if present. These tasks can be seen as an Analysis of Vari ...

This paper explores data assimilation methods in the context of Bayesian Calibration for fuel performance models. It compares deterministic and stochastic approaches, concentrating on the Generalized Linear Least Squares (GLLS) method and stochastic techni ...

We summarize what we consider to be the two main limitations of the "Estimands for Recurrent Event Endpoints in the Presence of a Terminal Event" (Schmidli et al. 2022). First, the authors did not give detailed guidance on how to choose an appropriate esti ...

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 ...

To understand how daylight gives shape and life to architectural spaces, whether existing or imagined, requires quantifying its dynamism and energy. Maintaining these details presents a challenge to simulation and analysis methods that flatten data into di ...

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg(2) over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI ...

A measurement is presented of the primary Lund jet plane (LJP) density in inclusive jet production in proton-proton collisions. The analysis uses 138 fb(-1) of data collected by the CMS experiment at root s = 13TeV. The LJP, a representation of the phase s ...

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

Stochastic vs. sensitivity-based integral parameter and nuclear data adjustments

Chattez avec Graph Search

Distribution Testing with a Confused Collector

Comparison of two methods for bioaerosol sampling and characterization in a low-biomass chamber environment

A setup for hard x-ray time-resolved resonant inelastic x-ray scattering at SwissFEL

Epidemic Learning: Boosting Decentralized Learning with Randomized Communication

Complex-order scale-invariant operators and self-similar processes

A Study on Gradient-based Meta-learning for Robust Deep Digital Twins

Infinite-width limit of deep linear neural networks

Center-aware Adversarial Augmentation for Single Domain Generalization

Extensions of Peer Prediction Incentive Mechanisms

Validation of semi-analytical, semi-empirical covariance matrices for two-point correlation function for early DESI data

Transportation-based functional ANOVA and PCA for covariance operators

Comparison of Bayesian Model Calibration Techniques for Future Application to Fuel Performance Behavior Models

We Need Subject Matter Expertise to Choose and Identify Causal Estimands: Comment on "Estimands for Recurrent Event Endpoints in the Presence of a Terminal Event"

An immersive virtual reality tool for assessing left and right unilateral spatial neglect

Traversing Time Dependent Light Fields for Daylight Glare Evaluation

Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument

Measurement of the primary Lund jet plane density in proton-proton collisions at √s=13 TeV

Robust discrete choice models with t-distributed kernel errors