Challenges and Issues on Artificial Hydrocarbon Networks: The Chemical Nature of Data-Driven Approaches - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2019

Challenges and Issues on Artificial Hydrocarbon Networks: The Chemical Nature of Data-Driven Approaches

Hiram Ponce
  • Fonction : Auteur
  • PersonId : 1052153

Résumé

Inspiration in nature has been widely explored, from macro to micro-scale. When looking into chemical phenomena, stability and organization are two properties that emerge. Recently, artificial hydrocarbon networks (AHN), a supervised learning method inspired in the inner structures and mechanisms of chemical compounds, have been proposed as a data-driven approach in artificial intelligence. AHN have been successfully applied in data-driven approaches, such as: regression and classification models, control systems, signal processing, and robotics. To do so, molecules –the basic units of information in AHN– play an important role in the stability, organization and interpretability of this method. Interpretability, saving computing resources, and predictability have been handled by AHN, as any other machine learning model. This short paper aims to highlight the challenges, issues and trends of artificial hydrocarbon networks as a data-driven method. Throughout this document, it presents a description of the main insights of AHN and the efforts to tackle interpretability and training acceleration. Potential applications and future trends on AHN are also discussed.
Fichier principal
Vignette du fichier
LXAI 2019 Abstract.pdf (100.19 Ko) Télécharger le fichier
Poster_Hiram_Ponce.pdf (2.82 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-02263834 , version 1 (05-08-2019)

Licence

Paternité

Identifiants

  • HAL Id : hal-02263834 , version 1

Citer

Hiram Ponce. Challenges and Issues on Artificial Hydrocarbon Networks: The Chemical Nature of Data-Driven Approaches. LatinX in AI Research at ICML 2019, Jun 2019, Long Beach, CA, United States. ⟨hal-02263834⟩
72 Consultations
56 Téléchargements

Partager

Gmail Facebook X LinkedIn More