Beam Measurements and Machine Learning at the CERN Large Hadron Collider

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A search is presented for fractionally charged particles with charges below (Formula presented), using their small energy loss in the tracking detector as a key variable to observe a signal. The analyzed dataset corresponds to an integrated luminosity of ( ...

Demographic fairness or equity is a crucial aspect of machine learning models, particularly in critical domains such as healthcare, where errors can have severe consequences. A fair model avoids making distinctions between groups with different sensitive o ...

An amplitude analysis of the Ds1(2460)+→Ds+π+π- transition is performed simultaneously in B0→D-Ds+π+π-, B+→D¯0Ds+π+π-, and B0→D*-Ds+π+π- decays. The study is based on a data sample of proton-proton collisions recorded with the LHCb detector at centre-of-ma ...

The sum-of-squares (SOS) approximation method is a technique used in optimization problems to derive lower bounds on the optimal value of an objective function. By representing the objective function as a sum of squares in a feature space, the SOS method t ...

By 'social learning,' in this article we refer to mechanisms for opinion formation and decision making over graphs and the study of how agents' decisions evolve dynamically through interactions with neighbors and the environment. The study of social learni ...

The increasing complexity of transformer models in artificial intelligence expands their computational costs, memory usage, and energy consumption. Hardware acceleration tackles the ensuing challenges by designing processors and accelerators tailored for t ...

Our understanding of the generalization capabilities of neural networks (NNs) is still incomplete. Prevailing explanations are based on implicit biases of gradient descent (GD) but they cannot account for the capabilities of models from gradient-free metho ...

A novel technique based on machine learning is introduced to reconstruct the decays of highly Lorentz boosted particles. Using an end-to-end deep learning strategy, the technique bypasses existing rule-based particle reconstruction methods typically used i ...

Cryogenic operation is the backbone of many cutting edge applications. Significant work has been done to characterize and model all cryogenic effects for creating a reliable, robust and efficient cryogenic design across a wide range of technologies and pro ...

Supplementary files containing datasets needed to reproduce the results of the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" by S. Choudhury et al. The code to use with these da ...

Data redundancy has been one of the most important problems in data-intensive applications such as data mining and machine learning. Removing data redundancy brings many benefits in efficient data updating, effective data storage, and error-free query proc ...

Despite the high number of investments for data-based models in the expansion of Industry 4.0, too little effort has been made to ensure the maintenance of those models. In a data-streaming environment, data-based models are subject to concept drifts. A co ...

In medical image segmentation, supervised deep networks' success comes at the cost of requiring abundant labeled data. While asking domain experts to annotate only one or a few of the cohort's images is feasible, annotating all available images is impracti ...

Specifying utility functions is a key step towards applying the discrete choice framework for understanding the behaviour processes that govern user choices. However, identifying the utility function specifications that best model and explain the observed ...

We demonstrate cryogenic switching devices based on HEMT technology for scalable quantum computer (QC) control and readout signal routing. The switches are implemented in a quantum well network design without metal contacts between gates, and exhibit extre ...

The design of user-level integrated energy systems is challenged by a variety of combinations of energy converters, complex cascade utilization of multiple energy flows, as well as sequential matching between stochastic energy resources and periodic energy ...

Ferroelectricity has made a huge impact on science and technology since Joseph Valasek (then a Ph.D. student at the University of Minnesota) discovered it in 1920, a little longer than 100 years ago. Whereas Dr. Valasek's original research was motivated by ...

An amplitude analysis of flavor-untagged B0s→J/ψp¯p decays is performed using a sample of 797±31 decays reconstructed with the LHCb detector. The data, collected in proton-proton collisions between 2011 and 2018, correspond to an integrated luminosity of 9 ...

We demonstrate single-stage thermo-optic Si3N4 interferometers with (46.1 +/- 2.5) dB average extinction ratio over 1460-1640 nm (approximate to 50x of typical devices). We analyze performance requirements for creating reconfigurable high-quality-factor re ...

Beam Measurements and Machine Learning at the CERN Large Hadron Collider

Chattez avec Graph Search

Search for Fractionally Charged Particles in Proton-Proton Collisions at (Formula presented)

Optimizing fairness and utility in healthcare machine learning models

Study of Ds1(2460)+→Ds+π+π- in B→D¯(*)Ds+π+π- decays

Theory and applications of the sum-of-squares technique

Statistical mechanics of deep learning

Socially Intelligent Networks: A framework for decision making over graphs

Accelerator-driven Data Arrangement to Minimize Transformers Run-time on Multi-core Architectures

Neural Redshift: Random Networks are not Random Functions

Reconstruction of decays to merged photons using end-to-end deep learning with domain continuation in the CMS detector

Overview of Cryogenic Operation in Nanoscale Technology Nodes

Supplementary datasets for the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" -Part 2

Validating functional redundancy with mixed generative adversarial networks

Data-based model maintenance in the era of industry 4.0: A methodology

Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation

Bayesian Automatic Relevance Determination for Utility Function Specification in Discrete Choice Models

Cryogenic InGaAs HEMT-Based Switches For Quantum Signal Routing

Energy hub-based optimal planning framework for user-level integrated energy systems: Considering synergistic effects under multiple uncertainties

Recent Advances in Piezoelectric Materials for Electromechanical Transducer Applications

Evidence for a New Structure in the J/ψp and J/ψ¯p Systems in B0s→J/ψp¯p Decays

Up to 50 dB Extinction in Broadband Single-Stage Thermo-Optic Mach-Zehnder Interferometers for Programmable Low-Loss Silicon Nitride Photonic Circuits