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This paper proposes a new theory and methodology to tackle the problem of unifying distributed analyses and inferences on shared parameters from multiple sources, into a single coherent inference. This surprisingly challenging problem…

Methodology · Statistics 2019-07-22 Hongsheng Dai , Murray Pollock , Gareth Roberts

Following their success in Computer Vision and other areas, deep learning techniques have recently become widely adopted in Music Information Retrieval (MIR) research. However, the majority of works aim to adopt and assess methods that have…

Computer Vision and Pattern Recognition · Computer Science 2018-05-04 Keunwoo Choi , György Fazekas , Kyunghyun Cho , Mark Sandler

Music accounts for a significant chunk of interest among various online activities. This is reflected by wide array of alternatives offered in music related web/mobile apps, information portals, featuring millions of artists, songs and…

Databases · Computer Science 2014-11-20 Shubhanshu Gupta

We use SMT technology to address a class of problems involving uninterpreted functions and nonlinear real arithmetic. In particular, we focus on problems commonly found in mathematical competitions, such as the International Mathematical…

Logic in Computer Science · Computer Science 2025-07-10 Chad E. Brown , Karel Chvalovský , Mikoláš Janota , Mirek Olšák , Stefan Ratschan

Advancements in the digital technologies have enabled researchers to develop a variety of Computational Music applications. Such applications are required to capture, process, and generate data related to music. Therefore, it is important…

Sound · Computer Science 2021-04-27 SeyyedPooya HekmatiAthar , Mohd Anwar

Mathematical software systems are becoming more and more important in pure and applied mathematics in order to deal with the complexity and scalability issues inherent in mathematics. In the last decades we have seen a cambric explosion of…

Mathematical Software · Computer Science 2020-02-13 Katja Bercic , Jacques Carette , William M. Farmer , Michael Kohlhase , Dennis Müller , Florian Rabe , Yasmine Sharoda

Mathematical oncology is an interdisciplinary research field where the mathematical sciences meet cancer research. Being situated at the intersection of these two fields makes mathematical oncology highly dynamic, as practicing researchers…

Physics and Society · Physics 2025-10-08 Kira Pugh , Linnéa Gyllingberg , Stanislav Stratiev , Sara Hamis

We deliver a call to arms for probabilistic numerical methods: algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such…

Numerical Analysis · Mathematics 2016-02-17 Philipp Hennig , Michael A Osborne , Mark Girolami

Multimodal music emotion recognition (MMER) is an emerging discipline in music information retrieval that has experienced a surge in interest in recent years. This survey provides a comprehensive overview of the current state-of-the-art in…

Multimedia · Computer Science 2025-04-29 Rashini Liyanarachchi , Aditya Joshi , Erik Meijering

The highest level of mathematics has traditionally been seen as a solitary endeavour, to produce a proof for review and acceptance by research peers. Mathematics is now at a remarkable inflexion point, with new technology radically…

Social and Information Networks · Computer Science 2013-05-07 Ursula Martin , Alison Pease

Cover song detection has been an active field in the Music Information Retrieval (MIR) community during the past decades. Most of the research community focused in solving it for a wide range of music genres with diverse characteristics.…

Information Retrieval · Computer Science 2024-04-16 Mickaël Arcos

Computing systems interacting with real-world processes must safely and reliably process uncertain data. The Monte Carlo method is a popular approach for computing with such uncertain values. This article introduces a framework for…

Beat and downbeat tracking models have improved significantly in recent years with the introduction of deep learning methods. However, despite these improvements, several challenges remain. Particularly, the adaptation of available models…

Sound · Computer Science 2023-04-17 Lucas S. Maia , Martín Rocamora , Luiz W. P. Biscainho , Magdalena Fuentes

The introduction of computational models in cardiovascular sciences has been progressively bringing new and unique tools for the investigation of the physiopathology. Together with the dramatic improvement of imaging and measuring devices…

Since the 60s, musicology has been increasingly impacted by computational tools in various ways, from systematic analysis approaches to modeling of creativity. This article presents a comprehensive assessment of the current state of…

Digital Libraries · Computer Science 2025-07-22 Jorge Junior Morgado Vega , Sachin Sharma , Federico Simonetta

Statistics experiences a storm around the perceived misuse and possible abuse of its methods in the context of the so-called reproducibility crisis. The methods and styles of quantification practiced in mathematical modelling rarely make it…

Methodology · Statistics 2019-08-20 Andrea Saltelli

Today, a massive amount of musical knowledge is stored in written form, with testimonies dated as far back as several centuries ago. In this work, we present different Natural Language Processing (NLP) approaches to harness the potential of…

Computation and Language · Computer Science 2018-07-09 Sergio Oramas , Luis Espinosa-Anke , Francisco Gómez , Xavier Serra

We present a scoping review of published literature on ethnomathematics and Indigenous mathematics as a step towards a goal to decolonize the prevailing Eurocentric view of the provenance of mathematics. Mathematical practices were…

History and Overview · Mathematics 2024-06-26 Hongzhang Xu , Rowena Ball

The growing of cities has resulted in innumerable technical and managerial challenges for public administrators such as energy consumption, pollution, urban mobility and even supervision of private and public spaces in an appropriate way.…

Monte Carlo simulations are based on the manipulation of random numbers to evaluate probable outcomes, with applicability in a variety of different fields. By assigning probabilities, which can be determined a priori, to various events, it…

Physics Education · Physics 2022-01-03 Parasuraman Swaminathan