Results 121 to 130 of about 103,187 (313)
Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Advanced Science, EarlyView.Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source
tascCODA: Bayesian Tree-Aggregated Analysis of Compositional Amplicon and Single-Cell Data. [PDF]
Front Genet, 2021 Ostner J, Carcy S, Müller CL.
europepmc +1 more source
MFPD: A Multiple Fungal Pathogen Detection Pipeline Across Diverse Habitats
Advanced Science, EarlyView.The MFPD pipeline integrates a comprehensive ITS reference database of fungal pathogens, optimized parameters, and algorithms tailored for both full‐length and subregion sequences that balance accuracy and computational efficiency; it enables high‐throughput, species‐level identification from amplicon sequencing data, supporting large‐scale ...
Yi Shen +13 more
wiley +1 more source
Unconstrained Nrf2 Bayesian phylogenetic tree and species tree [PDF]
, 2016 This is a TIFF picture of Unconstrained Nrf2 Bayesian phylogenetic tree and species ...
Lei Zhu (16642) +11 more
core +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
Advanced Science, EarlyView.The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
Particle Gibbs for Bayesian Additive Regression Trees
CoRR, 2015 Additive regression trees are flexible non-parametric models and popular off-the-shelf tools for real-world non-linear regression. In application domains, such as bioinformatics, where there is also demand for probabilistic predictions with measures of uncertainty, the Bayesian additive regression trees (BART) model, introduced by Chipman et al. (2010),
Lakshminarayanan, B, Roy, DM, Teh, YW
openaire +4 more sources
IntelLabs/bayesian-torch: Bayesian-Torch 0.5.0 [PDF]
<p>This release includes support for quantization of all the Bayesian Convolutional layers listed below in addition to Conv2dReparameterization and Conv2dFlipout.</p> <p>Conv1dReparameterization, Conv3dReparameterization ...
Michael Beale +5 more
core +1 more source
Bayesian tree for molecular data [PDF]
, 2018 Bayesian tree for MrBayes analysis using the molecular data ...
Bárcenas-Argüello, Maria Luisa +7 more
core +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Advanced Science, EarlyView.Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
Bayesian inference tree. [PDF]
, 2015 This tree was inferred from the mtDNA dataset. All of the Bayesian posterior probabilities (BPP) and NCBI numbers were shown.
Jia-Tang Li (786999) +8 more
core +1 more source