Работы, цитирующие эту работу

Работ: 5

Работа: On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Degradation Diagnosis (Short Paper)

1. Explaining the Deep Natural Language Processing by Mining Textual Interpretable Features

   Francesco Ventura, Salvatore Greco, Daniele Apiletti +1

   ПрепринтExplainable Artificial Intelligence (XAI)arXiv (Cornell University)2021Цитирований: 0

   ABIABI:AkademIndex/openalex/2021.preprint.000107

2. Deep Learning based Joint Fusion approach to exploit anatomical and functional brain information in Autism Spectrum Disorders

   Sara Saponaro, Francesca Lizzi, Giacomo Serra +5

   ПрепринтAutism Spectrum Disorder ResearchResearch Square2023Цитирований: 0

   ABIABI:AkademIndex/openalex/2023.preprint.000166

3. A robust and interpretable graph neural network-based protocol for predicting p-glycoprotein substrates

   Kuang-Cheng Hsu, Peihua Wang, Bo‐Han Su +1

   СтатьяComputational Drug Discovery MethodsBriefings in Bioinformatics2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.000817

4. Integrative analysis of transboundary land use conflicts in the Aral Sea Basin: A multi-scale assessment of drivers and strategies for sustainable management

   Kaiyue Luo, Alim Samat, Peijun Du +5

   СтатьяTransboundary Water Resource ManagementResources Environment and Sustainability2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.000909

5. Fabrication process analysis on Sb2(S Se1-)3-based material properties and solar cell performance via machine learning

   A. Olimov, T. M. Razykov, К. M. Kuchkarov +4

   СтатьяChalcogenide Semiconductor Thin FilmsThin Solid Films2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.004115