Výsledky vyhledávání - "Valdés, Julio J."

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Understanding the Structure of QM7b and QM9 Quantum Mechanical Datasets Using Unsupervised Learning

Autor: Valdés, Julio J., Tchagang, Alain B.

This paper explores the internal structure of two quantum mechanics datasets (QM7b, QM9), composed of several thousands of organic molecules and described in terms of electronic properties. Understanding the structure and characteristics of this kind

Externí odkaz: http://arxiv.org/abs/2309.15130

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Molecular Design Using Signal Processing and Machine Learning: Time-Frequency-like Representation and Forward Design

Autor: Tchagang, Alain B., Tewfik, Ahmed H., Valdés, Julio J.

Accumulation of molecular data obtained from quantum mechanics (QM) theories such as density functional theory (DFTQM) make it possible for machine learning (ML) to accelerate the discovery of new molecules, drugs, and materials. Models that combine

Externí odkaz: http://arxiv.org/abs/2004.10091

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Novel machine learning insights into the QM7b and QM9 quantum mechanics datasets.

Autor: Valdés, Julio J., Tchagang, Alain B.

Publikováno v: Journal of Computational Chemistry; 6/5/2024, Vol. 45 Issue 15, p1193-1214, 22p

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Potential energy savings from high-resolution sensor controls for LED lighting

Autor: Dikel, Erhan E., Newsham, Guy R., Xue, Henry, Valdés, Julio J.

Publikováno v: In Energy & Buildings 1 January 2018 158:43-53

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Data augmentation using reverb and noise in deep learning implementation of cough classification

Autor: Huq, Saiful, Xi, Pengcheng, Goubran, Rafik, Valdés, Julio J., Knoefel, Frank, Green, James R

The interest in automated analysis and classification of cough sounds has increased in recent years, partly due to the worldwide COVID19 pandemic. To train such classification models, a large dataset of cough sounds is needed, however, it remains cha

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______1674::1af438bb9744ab7bbce06f8094b833e9
https://nrc-publications.canada.ca/eng/view/object/?id=a005d39d-8dca-473d-967b-65f0c73185e2

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Data and knowledge visualization with virtual reality spaces, neural networks and rough sets: Application to cancer and geophysical prospecting data

Autor: Valdés, Julio J., Romero, Enrique, Barton, Alan J.

Publikováno v: In Expert Systems With Applications 15 December 2012 39(18):13193-13201

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Data driven study of estuary hypoxia

Autor: Hussain, Md Monwer, Durand, Guillaume, Coffin, Michael, Valdés, Julio J, Poirier, Luke

This paper presents a data driven study of dissolved oxygen times series collected in Atlantic Canada. The main motivation of presented work was to evaluate if machine learning techniques could help to understand and anticipate hypoxic episodes in nu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______1674::84cd058159ffdf01527c7792f2cc03d4
https://nrc-publications.canada.ca/eng/view/object/?id=0251a8fe-28d4-44df-95da-b03edacb5737

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