arXiv:2509. 00123v2 Announce Type: replace-cross Abstract: A fundamental challenge in microbial ecology is determining whether bacteria compete or cooperate in different environmental conditions.
By Oleksandr Cherednichenko, Josephine Solowiej-Wedderburn, Laura M. Carroll, Eric Libby
arXiv:2606. 07686v1 Announce Type: cross Abstract: Physics-Informed Neural Network (PINN) is a way of including knowledge in the form of equations in Machine Learning methods.
By Ravisha Rupasinghe, Rajith Vidanaarachchi, Asela Hevapathige, Sachith Seneviratne, Sen-Lin Tang, Saman Halgamuge
arXiv:2608. 06727v1 Announce Type: new Abstract: Transformer models for high-dimensional omics analysis process thousands of genes or pathways, although only a subset requires deep computation.
By Koushik Howlader, Tirtho Roy, Md Tauhidul Islam, Wei Le
Transformer models for high-dimensional omics analysis process thousands of genes or pathways, although only a subset requires deep computation. Mixture-of-Recursions (MoR) improves efficiency through adaptive token-choice or expert-choice routing.
arXiv:2606. 24995v1 Announce Type: new Abstract: Tabular foundation models (TFMs) achieve strong performance on microbiome abundance data, yet their robustness under realistic distribution shift remains poorly characterized.
By Giulia Perciballi, Ahmad Fall, Federica Granese, Edi Prifti, Jean-Daniel Zucker
arXiv:2608. 08182v1 Announce Type: cross Abstract: Machine learning models for MALDI-TOF mass spectrometry have shown considerable promise for clinical microbiology tasks such as microbial identification and antimicrobial resistance prediction.
By Alejandro L. Garc\'ia-Navarro, Carlos Sevilla-Salcedo, Bel\'en Rodr\'iguez-S\'anchez, Vanessa G\'omez-Verdejo