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Conformal Prediction methods have finite-sample distribution-free marginal coverage guarantees. However, they generally do not offer conditional coverage guarantees, which can be important for high-stakes decisions. In this paper, we…

Machine Learning · Statistics 2024-09-27 Ruijiang Gao , Mingzhang Yin , James McInerney , Nathan Kallus

Generative models are increasingly central to scientific workflows, yet their systematic use and interpretation require a proper understanding of their limitations through rigorous validation. Classic approaches struggle with scalability,…

Machine Learning · Statistics 2025-11-26 Pietro Cappelli , Gaia Grosso , Marco Letizia , Humberto Reyes-González , Marco Zanetti

This report summarizes the latest developments in the CTEQ-TEA global analysis of parton distribution functions (PDFs) in the nucleon. The focus is on recent NNLO fits to high-precision LHC data at 8 and 13 TeV, including Drell-Yan, jet,…

High Energy Physics - Phenomenology · Physics 2024-11-26 A. Ablat , A. Courtoy , S. Dulat , M. Guzzi , T. J. Hobbs , T. -J. Hou , J. Huston , K. Mohan , H. -W. Lin , P. Nadolsky , I. Sitiwaldi , K. Xie , M. Yan , C. -P. Yuan

Finding a good way to model probability densities is key to probabilistic inference. An ideal model should be able to concisely approximate any probability while being also compatible with two main operations: multiplications of two models…

Machine Learning · Computer Science 2021-11-29 Alessandro Rudi , Carlo Ciliberto

One of the problems of formal verification is that it is not functionally complete due the incompleteness of specifications. An implementation meeting an incomplete specification may still have a lot of bugs. In testing, this issue is…

Logic in Computer Science · Computer Science 2020-10-14 Eugene Goldberg

Searches for new physics will increasingly depend on identifying deviations from precision Standard Model (SM) predictions. Quantum Chromodynamics (QCD) will necessarily play a central role in this endeavor as it provides the framework for…

High Energy Physics - Phenomenology · Physics 2016-04-20 Aleksander Kusina , Florian Lyonnet , Fredrick I. Olness , Ingo Schienbein

A complete and rigorously validated open-source Python framework to automate point defect calculations using density functional theory has been developed. The framework provides an effective and efficient method for defect structure…

Materials Science · Physics 2021-04-01 Anuj Goyal , Prashun Gorai , Haowei Peng , Stephan Lany , Vladan Stevanovic

Conformal prediction can be used to construct prediction sets that cover the true outcome with a desired probability, but can sometimes lead to large prediction sets that are costly in practice. The most useful outcome is a singleton…

Machine Learning · Statistics 2026-02-05 Tao Wang , Yan Sun , Edgar Dobriban

Estimating software testability can crucially assist software managers to optimize test budgets and software quality. In this paper, we propose a new approach that radically differs from the traditional approach of pursuing testability…

Software Engineering · Computer Science 2023-08-01 Luca Guglielmo , Leonardo Mariani , Giovanni Denaro

An extension of the xFitter open-source program for QCD analyses is presented, allowing for a polynomial parameterization of the dependence of physical observables on theoretical parameters. This extension enables simultaneous determination…

High Energy Physics - Phenomenology · Physics 2024-12-03 XiaoMin Shen , Simone Amoroso , Jun Gao , Katerina Lipka , Oleksandr Zenaiev

We consider marked empirical processes indexed by a randomly projected functional covariate to construct goodness-of-fit tests for the functional linear model with scalar response. The test statistics are built from continuous functionals…

It is well-known that the verification of partial correctness properties of imperative programs can be reduced to the satisfiability problem for constrained Horn clauses (CHCs). However, state-of-the-art solvers for CHCs (CHC solvers) based…

Logic in Computer Science · Computer Science 2018-06-29 Emanuele De Angelis , Fabio Fioravanti , Alberto Pettorossi , Maurizio Proietti

To obtain the highest confidence on the correction of numerical simulation programs for the resolution of Partial Differential Equations (PDEs), one has to formalize the mathematical notions and results that allow to establish the soundness…

Logic in Computer Science · Computer Science 2024-10-03 François Clément , Vincent Martin

Self-adaptive systems (SASs) are capable of adjusting its behavior in response to meaningful changes in the operational con-text and itself. The adaptation needs to be performed automatically through self-managed reactions and…

Software Engineering · Computer Science 2017-04-06 Zhuoqun Yang , Zhi Jin , Zhi Li

Conformal Prediction (CP) is a popular method for uncertainty quantification with machine learning models. While conformal prediction provides probabilistic guarantees regarding the coverage of the true label, these guarantees are agnostic…

Machine Learning · Computer Science 2025-10-21 Aditya T. Vadlamani , Anutam Srinivasan , Pranav Maneriker , Ali Payani , Srinivasan Parthasarathy

Fuzzing consists of repeatedly testing an application with modified, or fuzzed, inputs with the goal of finding security vulnerabilities in input-parsing code. In this paper, we show how to automate the generation of an input grammar…

Artificial Intelligence · Computer Science 2017-01-26 Patrice Godefroid , Hila Peleg , Rishabh Singh

This is the second in a series of articles aimed at exploring the relationship between the complexity classes of P and NP. The research in this article aims to find conditions of an algorithmic nature that are necessary and sufficient to…

Computational Complexity · Computer Science 2023-11-07 Stepan G. Margaryan

Permutation tests are a distribution free way of performing hypothesis tests. These tests rely on the condition that the observed data are exchangeable among the groups being tested under the null hypothesis. This assumption is easily…

Methodology · Statistics 2017-12-14 Daniell Toth

Context: Test-driven development (TDD) is a widely employed software development practice that involves developing test cases based on requirements prior to writing the code. Although various methods for automated test case generation have…

Software Engineering · Computer Science 2025-04-02 Saranya Alagarsamy , Chakkrit Tantithamthavorn , Wannita Takerngsaksiri , Chetan Arora , Aldeida Aleti

We propose a new approach to testing conformance to a nondeterministic specification, in which testing proceeds only as long as increased test coverage is guaranteed.

Software Engineering · Computer Science 2009-10-07 Ernie Cohen
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