Time Series Analysis in Compressor-Based Machines: A Survey

F Forbicini, NOP Vago, P Fraternali - arxiv preprint arxiv:2402.17802, 2024 - arxiv.org
In both industrial and residential contexts, compressor-based machines, such as
refrigerators, HVAC systems, heat pumps and chillers, are essential to fulfil production and …

Deep multimodal networks for m-type star classification with paired spectrum and photometric image

J Gao, J Chen, J Wei, B Jiang… - Publications of the …, 2023 - iopscience.iop.org
Traditional stellar classification methods include spectral and photometric classification
separately. Although satisfactory results can be achieved, the accuracy could be improved …

[PDF][PDF] Inferring the Hubble constant from simulated lensed supernova images using machine learning methods

GFM Gonçalves - 2024 - repositorio-aberto.up.pt
Measures of distances in the early and late Universe can be used to constrain cosmological
properties, such as the Universe's expansion rate. However, measurements obtained with …

Comparison of Convolutional Neural Networks and Random Forest Classifiers for Strong Gravitational Lens Identification

M Kothuri, S Saigal… - Research Notes of the …, 2024 - iopscience.iop.org
Strong gravitational lenses have been instrumental in providing insight into various
astronomical problems, including analyzing the dark matter distribution of the universe …

[PDF][PDF] Multimodal multi-output ordinal regression for discovering gravitationally-lensed transients

NOP Vago, P Fraternali - ml4physicalsciences.github.io
Gravitational lenses are caused by massive bodies that distort space-time, bending light.
They can distort transients, such as Supernovae (SN), which are being studied extensively …

[PDF][PDF] Leveraging Machine Learning Techniques for Accurate Conversion Rate Prediction

A Petrov, D Zhao, J Wang, J Smith, S Volkov, D Ivanov - researchgate.net
Advancements in machine learning have transformed various industries, particularly in
marketing analytics, where accurate prediction of conversion rates is critical for optimizing …