Interpretability of Graph Neural Networks to Assess Effects of Global Change Drivers on Ecological Networks

Documenti analoghi

• Bipartite Graph Variational Auto-Encoder with Fair Latent Representation to Account for Sampling Bias in Ecological Networks
  di: Anakok, Emre, et al.
  Pubblicazione: (2024)
• Disentangling the structure of ecological bipartite networks from observation processes
  di: Anakok, Emre, et al.
  Pubblicazione: (2022)
• Common Structure Discovery in Collections of Bipartite Networks: Application to Pollination Systems
  di: Lacoste, Louis, et al.
  Pubblicazione: (2025)
• How Interpretable Are Interpretable Graph Neural Networks?
  di: Chen, Yongqiang, et al.
  Pubblicazione: (2024)
• Unveiling Global Interactive Patterns across Graphs: Towards Interpretable Graph Neural Networks
  di: Wang, Yuwen, et al.
  Pubblicazione: (2024)