Search alternatives:
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
cost optimization » dose optimization (Expand Search), robust optimization (Expand Search), codon optimization (Expand Search)
library based » laboratory based (Expand Search)
binary basic » binary mask (Expand Search)
basic model » based model (Expand Search), base model (Expand Search)
based cost » based cross (Expand Search), based case (Expand Search), based cohort (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
cost optimization » dose optimization (Expand Search), robust optimization (Expand Search), codon optimization (Expand Search)
library based » laboratory based (Expand Search)
binary basic » binary mask (Expand Search)
basic model » based model (Expand Search), base model (Expand Search)
based cost » based cross (Expand Search), based case (Expand Search), based cohort (Expand Search)
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A Practical Algorithm to Solve the Near-Congruence Problem for Rigid Molecules and Clusters
Published 2023“…We present an improved algorithm to solve the near-congruence problem for rigid molecules and clusters based on the iterative application of assignment and alignment steps with biased Euclidean costs. …”
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024“…Ultimately, the study advocates for the synergy of physics-based methods and ML to expedite the lead optimization process. …”
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024“…Ultimately, the study advocates for the synergy of physics-based methods and ML to expedite the lead optimization process. …”
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6
FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024“…Ultimately, the study advocates for the synergy of physics-based methods and ML to expedite the lead optimization process. …”
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7
FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024“…Ultimately, the study advocates for the synergy of physics-based methods and ML to expedite the lead optimization process. …”
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8
FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024“…Ultimately, the study advocates for the synergy of physics-based methods and ML to expedite the lead optimization process. …”
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024“…Ultimately, the study advocates for the synergy of physics-based methods and ML to expedite the lead optimization process. …”
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10
FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024“…Ultimately, the study advocates for the synergy of physics-based methods and ML to expedite the lead optimization process. …”
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Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment
Published 2019“…<div><p>An image classification algorithm based on adaptive feature weight updating is proposed to address the low classification accuracy of the current single-feature classification algorithms and simple multifeature fusion algorithms. …”
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Acceleration of Inverse Molecular Design by Using Predictive Techniques
Published 2019“…This study addresses one of the most important drawbacks inherently related to molecular searches in chemical compound space by greedy algorithms such as Best First Search and Genetic Algorithm, i.e., the large computational cost required to optimize one or more quantum-chemical properties. …”
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Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP
Published 2022“…In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. …”
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DataSheet1_Quantum-assisted fragment-based automated structure generator (QFASG) for small molecule design: an in vitro study.docx
Published 2024“…</p><p>Methods: We developed Quantum-assisted Fragment-based Automated Structure Generator (QFASG), a fully automated algorithm designed to construct ligands for a target protein using a library of molecular fragments. …”
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Supporting data for "clinical-oriented surgical planning based on finite element method and automate-generated surgical templates assisting the spinal surgery"
Published 2024“…Remaining algorithm needed was reimplemented from open-source libraries.…”
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hIPPYlib: An Extensible Software Framework for Large-scale Inverse Problems
Published 2019“…The key property of the algorithms implemented in hIPPYlib is that the solution is computed at a cost, measured in forward PDE solves, that is independent of the parameter dimension. …”
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Table_3_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.xlsx
Published 2023“…Another noteworthy function is the refinement design of the training set, in which G2P optimizes the training set based on the genetic diversity analysis of a studied population. …”
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Image_1_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.jpeg
Published 2023“…Another noteworthy function is the refinement design of the training set, in which G2P optimizes the training set based on the genetic diversity analysis of a studied population. …”