Green AI architectures: Navigating the security-sustainability paradox in critical infrastructure protection. [PDF]
Lee J +3 more
europepmc +1 more source
ABSTRACT Improving classification performance on imbalanced datasets remains a challenging problem in machine learning. Synthetic oversampling techniques such as SMOTE are widely used to address class imbalance; however, their random interpolation strategy often ignores structural data properties, which may affect classifier generalisation.
Jose L. Morillo‐Salas +3 more
wiley +1 more source
LAIOR: a hyperbolic neural ODE variational framework for interpretable single-cell manifold learning and trajectory inference. [PDF]
Fu Z, Fu J, Zhang K, Ran T, Chen C.
europepmc +1 more source
Machine Learning of Personal Repertoires From Public T Cell Receptors
ABSTRACT The T‐cell receptor (TCR) repertoire records an individual's immunological history, but most unique CDR3 sequences in any one person are private and uninformative about anyone else. A small subset, however, recurs predictably across unrelated donors.
Or Malca, Alona Zilberberg, Sol Efroni
wiley +1 more source
ABSTRACT Deep generative models, particularly denoising diffusion models, have achieved remarkable success in high‐fidelity generation of architected microstructures with desired properties and styles. However, these recent methods typically rely on conditional training mechanisms that require extensive labeled data.
Weipeng Xu +5 more
wiley +1 more source
GRNFormer: accurate gene regulatory network inference using graph transformer. [PDF]
Hegde A, Cheng J.
europepmc +1 more source
HiSTaR: identifying spatial domains with hierarchical spatial transcriptomics variational autoencoder. [PDF]
Yu J, Yuan J, Yi Q, Ye Z, Xu P, Liu W.
europepmc +1 more source
Histopathological Assessment of Myocardial Ischemia-Reperfusion Injury Using Transformer-Based Artificial Intelligence: Model Comparison Study. [PDF]
Liu C, Xu M, Lv Y, Zhu Z, Pan Y, Wang Y.
europepmc +1 more source
scZiva: imputation method for single-cell RNA-seq data with zero-inflated variational autoencoder. [PDF]
Vo LT, Le VV, Ha QT, Nguyen AQ.
europepmc +1 more source
Applications of AI to single-cell and spatial transcriptomics: current state-of-the-art and challenges. [PDF]
Tchatchoua Ngassam B +4 more
europepmc +1 more source

