neural networks
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The work and the provided methodology provide a significant improvement in facies classification.
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In the complete paper, the authors generate a model by using an artificial-neural-network (ANN) technique to predict both capillary pressure and relative permeability from resistivity.
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Advances during the past decade in using convolutional neural networks for visual recognition of discriminately different objects means that now object recognition can be achieved to a significant extent.
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The complete paper explores the use of multilevel derivative-free optimization for history matching, with model properties described using principal component analysis (PCA) -based parameterization techniques.
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This paper describes an accurate, three-step, machine-learning-based early warning system that has been used to monitor production and guide strategy in the Shengli field.
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Here are some thoughts on recent discussions around natural-language-processing transformer models being too big to put into production and a dive into how they have been shipped at Monzo using the HuggingFace library.
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Even the most powerful computers are still no match for the human brain when it comes to pattern recognition, risk management, and other similarly complex tasks. A new approach, however, could enable parallel computation with light, simulating the way neurons respond in the human brain.
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Hamiltonian neural networks draw inspiration from Hamiltonian mechanics, a branch of physics concerned with conservation laws and invariances. By construction, these models learn conservation laws from data, revealing major advantages over regular neural networks on a variety of physics problems.
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Random Forest and Neural Network are the two widely used machine-learning algorithms. What is the difference between the two approaches? When should one use Neural Network or Random Forest?
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This paper discusses how machine learning by use of multiple linear regression and a neural network was used to optimize completions and well designs in the Duvernay shale.