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pro vyhledávání: '"Joseph, Manu"'
Querying databases for the right information is a time consuming and error-prone task and often requires experienced professionals for the job. Furthermore, the user needs to have some prior knowledge about the database. There have been various effor
Externí odkaz:
http://arxiv.org/abs/2210.08532
Autor:
Dhandekar, Pulah, Joseph, Manu
Aspect Based Sentiment Analysis is the most granular form of sentiment analysis that can be performed on the documents / sentences. Besides delivering the most insights at a finer grain, it also poses equally daunting challenges. One of them being th
Externí odkaz:
http://arxiv.org/abs/2210.06829
Autor:
Joseph, Manu, Lalwani, Varchita
Prognostics and Health Management (PHM) is an emerging field which has received much attention from the manufacturing industry because of the benefits and efficiencies it brings to the table. And Remaining Useful Life (RUL) prediction is at the heart
Externí odkaz:
http://arxiv.org/abs/2208.08388
Autor:
Joseph, Manu, Raj, Harsh
We propose a novel high-performance, interpretable, and parameter \& computationally efficient deep learning architecture for tabular data, Gated Adaptive Network for Deep Automated Learning of Features (GANDALF). GANDALF relies on a new tabular proc
Externí odkaz:
http://arxiv.org/abs/2207.08548
Autor:
Joseph, Manu
In spite of showing unreasonable effectiveness in modalities like Text and Image, Deep Learning has always lagged Gradient Boosting in tabular data - both in popularity and performance. But recently there have been newer models created specifically f
Externí odkaz:
http://arxiv.org/abs/2104.13638
Autor:
Archana, MG, Sreekutty, J, Syama, HP, Joseph, Manu M, Anusree, KS, Unnikrishnan, BS, Preethi, GU, Reshma, PL, Sreelekha, TT
Publikováno v:
In Journal of Drug Delivery Science and Technology February 2023 80
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Akademický článek
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