Interpretability of Graph Neural Networks to Assess Effects of Global Change Drivers on Ecological Networks
Fuente:
arXiv
Saved in:
| Main Authors: | Anakok, Emre, Barbillon, Pierre, Fontaine, Colin, Thebault, Elisa |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Bipartite Graph Variational Auto-Encoder with Fair Latent Representation to Account for Sampling Bias in Ecological Networks
by: Anakok, Emre, et al.
Published: (2024)
by: Anakok, Emre, et al.
Published: (2024)
Disentangling the structure of ecological bipartite networks from observation processes
by: Anakok, Emre, et al.
Published: (2022)
by: Anakok, Emre, et al.
Published: (2022)
Common Structure Discovery in Collections of Bipartite Networks: Application to Pollination Systems
by: Lacoste, Louis, et al.
Published: (2025)
by: Lacoste, Louis, et al.
Published: (2025)
How Interpretable Are Interpretable Graph Neural Networks?
by: Chen, Yongqiang, et al.
Published: (2024)
by: Chen, Yongqiang, et al.
Published: (2024)
Unveiling Global Interactive Patterns across Graphs: Towards Interpretable Graph Neural Networks
by: Wang, Yuwen, et al.
Published: (2024)
by: Wang, Yuwen, et al.
Published: (2024)
Faithful Interpretation for Graph Neural Networks
by: Hu, Lijie, et al.
Published: (2024)
by: Hu, Lijie, et al.
Published: (2024)
HyperSBINN: A Hypernetwork-Enhanced Systems Biology-Informed Neural Network for Efficient Drug Cardiosafety Assessment
by: Soukarieh, Inass, et al.
Published: (2024)
by: Soukarieh, Inass, et al.
Published: (2024)
Interpreting Temporal Graph Neural Networks with Koopman Theory
by: Guerra, Michele, et al.
Published: (2024)
by: Guerra, Michele, et al.
Published: (2024)
Interpretable Graph Neural Networks for Heterogeneous Tabular Data
by: Alkhatib, Amr, et al.
Published: (2024)
by: Alkhatib, Amr, et al.
Published: (2024)
Graph Structure Learning with Interpretable Bayesian Neural Networks
by: Wasserman, Max, et al.
Published: (2024)
by: Wasserman, Max, et al.
Published: (2024)
GIN-Graph: A Generative Interpretation Network for Model-Level Explanation of Graph Neural Networks
by: Yue, Xiao, et al.
Published: (2025)
by: Yue, Xiao, et al.
Published: (2025)
SIC: Similarity-Based Interpretable Image Classification with Neural Networks
by: Wolf, Tom Nuno, et al.
Published: (2025)
by: Wolf, Tom Nuno, et al.
Published: (2025)
Fusion of Graph Neural Networks via Optimal Transport
by: Ormaniec, Weronika, et al.
Published: (2025)
by: Ormaniec, Weronika, et al.
Published: (2025)
Factor Graph-based Interpretable Neural Networks
by: Li, Yicong, et al.
Published: (2025)
by: Li, Yicong, et al.
Published: (2025)
Interpretable Graph Neural Networks for Tabular Data
by: Alkhatib, Amr, et al.
Published: (2023)
by: Alkhatib, Amr, et al.
Published: (2023)
The Interpretable and Effective Graph Neural Additive Networks
by: Bechler-Speicher, Maya, et al.
Published: (2024)
by: Bechler-Speicher, Maya, et al.
Published: (2024)
Population trends and variability within bird communities are amplified by intense land use
by: Josquin Guerber, et al.
Published: (2026)
by: Josquin Guerber, et al.
Published: (2026)
Global-Local Graph Neural Networks for Node-Classification
by: Eliasof, Moshe, et al.
Published: (2024)
by: Eliasof, Moshe, et al.
Published: (2024)
From GNNs to Trees: Multi-Granular Interpretability for Graph Neural Networks
by: Yang, Jie, et al.
Published: (2025)
by: Yang, Jie, et al.
Published: (2025)
A Generalized Tikhonov Layer for Interpretable-by-design Graph Neural Networks
by: Tremblay, Nicolas, et al.
Published: (2026)
by: Tremblay, Nicolas, et al.
Published: (2026)
Uncertainty Quantification in CNN Through the Bootstrap of Convex Neural Networks
by: Du, Hongfei, et al.
Published: (2026)
by: Du, Hongfei, et al.
Published: (2026)
Graph Coordinates and Conventional Neural Networks -- An Alternative for Graph Neural Networks
by: Qin, Zheyi, et al.
Published: (2023)
by: Qin, Zheyi, et al.
Published: (2023)
GRAFT: Auditing Graph Neural Networks via Global Feature Attribution
by: Sahoo, Rishi Raj, et al.
Published: (2026)
by: Sahoo, Rishi Raj, et al.
Published: (2026)
SNNAX -- Spiking Neural Networks in JAX
by: Lohoff, Jamie, et al.
Published: (2024)
by: Lohoff, Jamie, et al.
Published: (2024)
Review of blockchain application with Graph Neural Networks, Graph Convolutional Networks and Convolutional Neural Networks
by: Ancelotti, Amy, et al.
Published: (2024)
by: Ancelotti, Amy, et al.
Published: (2024)
FIGNN: Feature-Specific Interpretability for Graph Neural Network Surrogate Models
by: Raut, Riddhiman, et al.
Published: (2025)
by: Raut, Riddhiman, et al.
Published: (2025)
Framework GNN-AID: Graph Neural Network Analysis Interpretation and Defense
by: Lukyanov, Kirill, et al.
Published: (2025)
by: Lukyanov, Kirill, et al.
Published: (2025)
SIG: Efficient Self-Interpretable Graph Neural Network for Continuous-time Dynamic Graphs
by: Fang, Lanting, et al.
Published: (2024)
by: Fang, Lanting, et al.
Published: (2024)
Fragment-Wise Interpretability in Graph Neural Networks via Molecule Decomposition and Contribution Analysis
by: Musiał, Sebastian, et al.
Published: (2025)
by: Musiał, Sebastian, et al.
Published: (2025)
Incorporating Retrieval-based Causal Learning with Information Bottlenecks for Interpretable Graph Neural Networks
by: Rao, Jiahua, et al.
Published: (2024)
by: Rao, Jiahua, et al.
Published: (2024)
Ligandformer: A Graph Neural Network for Predicting Compound Property with Robust Interpretation
by: Guo, Jinjiang, et al.
Published: (2022)
by: Guo, Jinjiang, et al.
Published: (2022)
On the Interpretability of Quantum Neural Networks
by: Pira, Lirandë, et al.
Published: (2023)
by: Pira, Lirandë, et al.
Published: (2023)
The Butterfly Effect: Neural Network Training Trajectories Are Highly Sensitive to Initial Conditions
by: Kwok, Devin, et al.
Published: (2025)
by: Kwok, Devin, et al.
Published: (2025)
Designing Graph Convolutional Neural Networks for Discrete Choice with Network Effects
by: Villarraga, Daniel F., et al.
Published: (2025)
by: Villarraga, Daniel F., et al.
Published: (2025)
Global Confidence Degree Based Graph Neural Network for Financial Fraud Detection
by: Liu, Jiaxun, et al.
Published: (2024)
by: Liu, Jiaxun, et al.
Published: (2024)
Eddy-Resolving Global Ocean Forecasting with Multi-Scale Graph Neural Networks
by: Hirabayashi, Yuta, et al.
Published: (2026)
by: Hirabayashi, Yuta, et al.
Published: (2026)
Interpreting Deep Neural Networks with the Package innsight
by: Koenen, Niklas, et al.
Published: (2023)
by: Koenen, Niklas, et al.
Published: (2023)
CONFINE: Conformal Prediction for Interpretable Neural Networks
by: Huang, Linhui, et al.
Published: (2024)
by: Huang, Linhui, et al.
Published: (2024)
Zero-Shot Temporal Resolution Domain Adaptation for Spiking Neural Networks
by: Karilanova, Sanja, et al.
Published: (2024)
by: Karilanova, Sanja, et al.
Published: (2024)
Time-Aware and Transition-Semantic Graph Neural Networks for Interpretable Predictive Business Process Monitoring
by: Wang, Fang, et al.
Published: (2025)
by: Wang, Fang, et al.
Published: (2025)
Similar Items
-
Bipartite Graph Variational Auto-Encoder with Fair Latent Representation to Account for Sampling Bias in Ecological Networks
by: Anakok, Emre, et al.
Published: (2024) -
Disentangling the structure of ecological bipartite networks from observation processes
by: Anakok, Emre, et al.
Published: (2022) -
Common Structure Discovery in Collections of Bipartite Networks: Application to Pollination Systems
by: Lacoste, Louis, et al.
Published: (2025) -
How Interpretable Are Interpretable Graph Neural Networks?
by: Chen, Yongqiang, et al.
Published: (2024) -
Unveiling Global Interactive Patterns across Graphs: Towards Interpretable Graph Neural Networks
by: Wang, Yuwen, et al.
Published: (2024)