Cargando…
A Perspective on Explanations of Molecular Prediction Models
[Image: see text] Chemists can be skeptical in using deep learning (DL) in decision making, due to the lack of interpretability in “black-box” models. Explainable artificial intelligence (XAI) is a branch of artificial intelligence (AI) which addresses this drawback by providing tools to interpret D...
Autores principales: | Wellawatte, Geemi P., Gandhi, Heta A., Seshadri, Aditi, White, Andrew D. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10134429/ https://www.ncbi.nlm.nih.gov/pubmed/36972469 http://dx.doi.org/10.1021/acs.jctc.2c01235 |
Ejemplares similares
-
Model agnostic generation of counterfactual explanations for molecules
por: Wellawatte, Geemi P., et al.
Publicado: (2022) -
Graph neural network based coarse-grained mapping prediction
por: Li, Zhiheng, et al.
Publicado: (2020) -
Correction: Graph neural network based coarse-grained mapping prediction
por: Li, Zhiheng, et al.
Publicado: (2021) -
Assessment of chemistry knowledge in large language models that generate code
por: White, Andrew D., et al.
Publicado: (2023) -
Therapeutic itineraries and explanations for tuberculosis: an indigenous perspective
por: Nogueira, Laura Maria Vidal, et al.
Publicado: (2016)