CALL FOR PAPERS   The Seventh International Econometric Conference of Vietnam – ECONVN2024   Ho Chi Minh City, Vietnam, January 09-11, 2024   Main theme:   PARTIAL IDENTIFICATION IN ECONOMETRICS AND RELATED TOPICS   We have witnessed recent developments in the partial identification approach in econometrics since the early 1990s. Therefore, the Seventh International […]

                                    “en la senda de Sadosky” ¡Aún tenés tiempo de reservar tu vacante! Estimados/as,  Les acercamos información sobre los cursos que se dictarán virtualmente en el campus de SADIO.   Para más información sobre los cursos click aquí.    Esperamos que sea de su interés y agradecemos la difusión que pueda darle.    Saludos cordiales.  […]

10th INTERNATIONAL GRAN CANARIA SCHOOL ON DEEP LEARNING DeepLearn 2023 Summer Las Palmas de Gran Canaria, Spain July 17-21, 2023 https://deeplearn.irdta.eu/2023su/ ************************************************************************ Co-organized by: University of Las Palmas de Gran Canaria Institute for Research Development, Training and Advice – IRDTA Brussels/London ************************************************************************ Early registration: April 6, 2023 ************************************************************************ FRAMEWORK: DeepLearn 2023 Summer is part of […]

ICIAP 2023 – 22nd International Conference on Image Analysis and Processing https://www.iciap2023.org CALL TUTORIALS The 22nd International Conference on Image Analysis And Processing (ICIAP 2023) to be held in Udine, Italy will host tutorials on topics related to research in Computer Vision, Machine Learning, Image Processing, Medical Imaging and related fields. Tutorial topics should be […]

Call for Papers: Emerging Trends and Applications of Deep Learning for Biomedical Data Analysis https://www.springer.com/journal/11042/updates/24678968 Summary and Scope Nowadays, Deep learning (DL) becomes an attractive research topic for many researchers from academia and industry communities. Indeed, DL algorithms have demonstrated their ability to train learning models for large-volume data as well as their performances compared […]