Search alternatives:
robust optimization » process optimization (Expand Search), robust estimation (Expand Search), joint optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
library based » laboratory based (Expand Search)
based robust » based probes (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data codon » data code (Expand Search), data codes (Expand Search), data codings (Expand Search)
robust optimization » process optimization (Expand Search), robust estimation (Expand Search), joint optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
library based » laboratory based (Expand Search)
based robust » based probes (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data codon » data code (Expand Search), data codes (Expand Search), data codings (Expand Search)
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21
Code
Published 2025“…</p><p><br></p><p dir="ltr">This architecture was implemented using the PyTorch library and trained using cross-entropy loss. The model was optimized to classify RNA sequences, achieving robust performance across multiple test sets.…”
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22
Core data
Published 2025“…</p><p><br></p><p dir="ltr">This architecture was implemented using the PyTorch library and trained using cross-entropy loss. The model was optimized to classify RNA sequences, achieving robust performance across multiple test sets.…”
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23
Minisymposterium: Muq-Hippylib: A Bayesian Inference Software Framework Integrating Data with Complex Predictive Models under Uncertainty
Published 2021“…By integrating these two libraries, we created a robust, scalable, efficient and productive software framework that realizes the benefits of each to tackle complex large-scale Bayesian inverse problems across a broad spectrum of scientific and engineering areas.…”
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24
SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion
Published 2020“…By integrating these two libraries, we created a robust, scalable, and efficient software framework that realizes the benefits of each to tackle complex large-scale Bayesian inverse problems across a broad spectrum of scientific and engineering areas.…”
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25
SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion
Published 2020“…By integrating these two libraries, we created a robust, scalable, and efficient software framework that realizes the benefits of each to tackle complex large-scale Bayesian inverse problems across a broad spectrum of scientific and engineering areas.…”