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Related papers: VecAmpFit: vectorized amplitude-analysis fitting l…

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The massive increase in the data volume and dataset availability for analysts compels researchers to focus on data content and select high-quality datasets to enhance the performance of analytics operators. While selecting high-quality data…

Machine Learning · Computer Science 2025-08-25 Andreas Loizou , Dimitrios Tsoumakos

Vertical federated learning (VFL) has emerged as a paradigm for collaborative model estimation across multiple clients, each holding a distinct set of covariates. This paper introduces the first comprehensive framework for fitting Bayesian…

Computation · Statistics 2024-05-08 Conor Hassan , Matthew Sutton , Antonietta Mira , Kerrie Mengersen

Multivariate linear mixed models (mvLMMs) have been widely used in many areas of genetics, and have attracted considerable recent interest in genome-wide association studies (GWASs). However, fitting mvLMMs is computationally non-trivial,…

Quantitative Methods · Quantitative Biology 2013-09-13 Xiang Zhou , Matthew Stephens

Wideband power amplifiers exhibit complex nonlinear and memory effects that challenge traditional behavioral modeling approaches. This paper proposes a novel amplitude conditioned long short-term memory (AC-LSTM) network that introduces…

Machine Learning · Computer Science 2026-03-03 Abdelrahman Abdelsalam , You Fei

We present MadAnalysis 5, an analysis package dedicated to phenomenological studies of simulated collisions occurring in high-energy physics experiments. Within this framework, users are invited, through a user-friendly Python interpreter,…

High Energy Physics - Phenomenology · Physics 2015-05-27 Eric Conte , Béranger Dumont , Benjamin Fuks , Thibaut Schmitt

As developers of libraries implementing interval arithmetic, we faced the same difficulties when it came to testing our libraries. What must be tested? How can we devise relevant test cases for unit testing? How can we ensure a high (and…

Numerical Analysis · Mathematics 2022-05-25 Nathalie Revol , Luis Benet , Luca Ferranti , Sergei Zhilin

A new and automated method is presented for the analysis of high-resolution absorption spectra. Three established numerical methods are unified into one "artificial intelligence" process: a genetic algorithm (GVPFIT); non-linear…

Instrumentation and Methods for Astrophysics · Physics 2017-02-01 Matthew B. Bainbridge , John K. Webb

Belle II is a $B$ factory experiment aiming to start physics data taking in 2017. It is currently being set up at the SuperKEKB accelerator at the KEK facility in Tsukuba (Japan), an asymmetric $e^+e^-$ collider which aims to achieve an…

Instrumentation and Detectors · Physics 2019-08-14 Tobias Schlüter

Helicity amplitudes calculations with the program PHACT are explained. Some examples of their application in WPHACT and SIXPHACT MC's are given.

High Energy Physics - Phenomenology · Physics 2007-05-23 Alessandro Ballestrero

As large language models (LLMs) are increasingly deployed for software engineering, constructing high-quality benchmarks is crucial for evaluating not just the functional correctness, but also the formal verifiability of generated code.…

Machine Learning · Computer Science 2026-05-22 Yifan Bai , Xiaoyang Liu , Zihao Mou , Guihong Wang , Jian Yu , Shuhan Xie , Yantao Li , Yangyu Zhang , Jingwei Liang , Tao Luo

This paper is first devoted to study an adaptive wavelet based estimator of the long memory parameter for linear processes in a general semi-parametric frame. This is an extension of Bardet {\it et al.} (2008) which only concerned Gaussian…

Statistics Theory · Mathematics 2010-12-08 Jean-Marc Bardet , Hatem Bibi

The analysis of astronomical interferometric data is often performed on the images obtained after deconvolution of the interferometer's point spread function (PSF). This strategy can be understood (especially for cases of sparse arrays) as…

Instrumentation and Methods for Astrophysics · Physics 2015-06-18 I. Marti-Vidal , W. H. T. Vlemmings , S. Muller , S. Casey

To quantify the complexity of a system, entropy-based methods have received considerable critical attentions in real-world data analysis. Among numerous entropy algorithms, amplitude-based formulas, represented by Sample Entropy, suffer…

Signal Processing · Electrical Eng. & Systems 2022-01-12 Hongjian Xiao , Danilo P. Mandic

Vector architectures lack tools for research. Consider the gem5 simulator, which is possibly the leading platform for computer-system architecture research. Unfortunately, gem5 does not have an available distribution that includes a…

The Laura++ software package is designed for performing fits of amplitude models to data from decays of spin-0 particles into final states containing three spin-0 particles - so-called Dalitz-plot analysis. An overview of the amplitude…

Data Analysis, Statistics and Probability · Physics 2016-05-30 Thomas Latham

Linear systems of equations can be found in various mathematical domains, as well as in the field of machine learning. By employing noisy intermediate-scale quantum devices, variational solvers promise to accelerate finding solutions for…

Quantum computing has a potential to accelerate the data processing efficiency, especially in machine learning, by exploiting special features such as the quantum interference. The major challenge in this application is that, in general,…

Nonlinear Mixed Effects models (NLME) models are widely used in pharmacometrics and related fields to analyze hierarchical and longitudinal data. However, as the number of parameters and random effects increases, traditional methods for…

Methodology · Statistics 2026-04-30 Mohamed Tarek , Pedro Afonso

Despite the lack of important functions supported only by legacy applications, the current VO-compatible tools have enough capabilities to allow powerful analysis of stellar spectra using both public archives and local proprietary data. We…

Instrumentation and Methods for Astrophysics · Physics 2011-12-14 Petr Škoda

This paper demonstrates that a progressively aligned language model can effectively bridge frozen vision encoders and large language models (LLMs). While the fundamental architecture and pre-training methods of vision encoders and LLMs have…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Junfei Xiao , Zheng Xu , Alan Yuille , Shen Yan , Boyu Wang