Ana María Martínez

Harvard University Press — United States

Computer Science · Physical Sciences

13h-index428citations85works2.02yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Bayesian Modeling and Causal Inference(23), Libraries, Manuscripts, and Books(9), Data Mining Algorithms and Applications(8), Machine Learning and Data Classification(8), Spanish Linguistics and Language Studies(6)

Publications85 total

Energy at the fair: County fair sponsorship patterns from the energy sector in the United States
Energy Research & Social Science·2025Open Access
GHS-OBAT: Global, open building attribute data reporting age, function, height and compactness at footprint level
Data in Brief·2025· 2 citedOpen Access
An Updated Simplified Energy Yield Model for Recent Photovoltaic Module Technologies
Progress in Photovoltaics Research and Applications·2025· 4 citedOpen Access
TOWARDS A PAN-EU BUILDING FOOTPRINT MAP BASED ON THE HIERARCHICAL CONFLATION OF OPEN DATASETS: THE DIGITAL BUILDING STOCK MODEL - DBSM
˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences·2023· 8 citedOpen Access
Guía de entornos caminables seguros: Lineamientos de diseño para el acceso a equipamientos urbanos y al transporte público en ciudades mexicanas
2022· 2 citedOpen Access
Analyzing concept drift: A case study in the financial sector
Intelligent Data Analysis·2020· 16 citedOpen Access
Evolución química del agua en un ambiente silicoclástico salino costero
2019
AMIDST: A Java toolbox for scalable probabilistic machine learning
Knowledge-Based Systems·2018· 14 citedOpen Access
Estudio sobre la situación de la vivienda pública en la Comunitat Valenciana
2018
Enseñanza del principio multiplicativo por profesores en formación para primaria
2018
Comprensión de la media ponderada por docentes en formación para primaria
2017
Scaling up Bayesian variational inference using distributed computing clusters
International Journal of Approximate Reasoning·2017· 14 cited
AMIDST: a Java Toolbox for Scalable Probabilistic Machine Learning
arXiv (Cornell University)·2017· 3 citedOpen Access
MAP inference in dynamic hybrid Bayesian networks
Progress in Artificial Intelligence·2017· 7 citedOpen Access
Comprensión de promedios por docentes en formación
2017
Financial Data Analysis with PGMs Using AMIDST
2016· 7 cited
Sample-Based Attribute Selective A$n$ DE for Large Data
IEEE Transactions on Knowledge and Data Engineering·2016· 26 cited
d-VMP: Distributed Variational Message Passing
VBN Forskningsportal (Aalborg Universitet)·2016· 7 citedOpen Access
Scalable MAP inference in Bayesian networks based on a Map-Reduce approach
VBN Forskningsportal (Aalborg Universitet)·2016Open Access
Probabilistic Graphical Models on Multi-Core CPUs Using Java 8
IEEE Computational Intelligence Magazine·2016· 13 citedOpen Access
page 1 of 5Next →

Frequent Co-authors

Helge Langseth(14), Thomas D. Nielsen(14), Andrés R. Masegosa(13), Antonio Salmerón(13), Anders L. Madsen(12), Darío Ramos-López(11), M. Julia Flores(9), José A. Gámez(9), Geoffrey I. Webb(5), José M. Puerta(5), Hanen Borchani(5), Shenglei Chen(4), Rafael Cabañas(4), María Laura Caminotti(4), Antonio Fernández(3), Edgardo Alberto Stubbs(3), Limin Wang(2), Ramón Sáez(2), Norma Ethel Mangiaterra(2), Pietro Florio(2)