Cover Image

Inductive inference of gradient-boosted decision trees on graphs for insurance fraud detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Vandervorst, Félix, Deprez, Bruno, Verbeke, Wouter, Verdonck, Tim
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Social and Information Networks
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

GARG-AML against Smurfing: A Scalable and Interpretable Graph-Based Framework for Anti-Money Laundering
by: Deprez, Bruno, et al.
Published: (2025)

Network Analytics for Anti-Money Laundering -- A Systematic Literature Review and Experimental Evaluation
by: Deprez, Bruno, et al.
Published: (2024)

Is TabPFN the Silver Bullet for Insurance Pricing?
by: Deprez, Bruno, et al.
Published: (2026)

Optimizing Treatment Allocation in the Presence of Interference
by: Caljon, Daan, et al.
Published: (2024)

Advances in Continual Graph Learning for Anti-Money Laundering Systems: A Comprehensive Review
by: Deprez, Bruno, et al.
Published: (2025)

Attention is all you need for boosting graph convolutional neural network
by: Wu, Yinwei
Published: (2024)

Beyond symmetrization: effective adjacency matrices and renormalization for (un)singed directed graphs
by: de Resende, Bruno Messias Farias
Published: (2024)

Towards Faster Graph Partitioning via Pre-training and Inductive Inference
by: Qin, Meng, et al.
Published: (2024)

Community and hyperedge inference in multiple hypergraphs
by: Ni, Li, et al.
Published: (2025)

Node Classification in Random Trees
by: Nuijten, Wouter W. L., et al.
Published: (2023)

Model inference for ranking from pairwise comparisons
by: Catalina, Daniel Sánchez, et al.
Published: (2025)

Inductive Knowledge Graph Completion with GNNs and Rules: An Analysis
by: Anil, Akash, et al.
Published: (2023)

Machine learning of network inference enhancement from noisy measurements
by: Wu, Kai, et al.
Published: (2023)

Sources of Gain: Decomposing Performance in Conditional Average Dose Response Estimation
by: Bockel-Rickermann, Christopher, et al.
Published: (2024)

Predicting the structure of dynamic graphs
by: Kandanaarachchi, Sevvandi, et al.
Published: (2024)

The G-invariant graph Laplacian
by: Rosen, Eitan, et al.
Published: (2023)

Haar-Laplacian for directed graphs
by: Badea, Theodor-Adrian, et al.
Published: (2024)

Estimating the history of a random recursive tree
by: Briend, Simon, et al.
Published: (2024)

Discriminative community detection for multiplex networks
by: Ortiz-Bouza, Meiby, et al.
Published: (2024)

Community detection robustness of graph neural networks
by: Goel, Jaidev, et al.
Published: (2025)

Deep learning for dynamic graphs: models and benchmarks
by: Gravina, Alessio, et al.
Published: (2023)

A survey of dynamic graph neural networks
by: Zheng, Yanping, et al.
Published: (2024)

Community detection by spectral methods in multi-layer networks
by: Qing, Huan
Published: (2024)

Modularity aided consistent attributed graph clustering via coarsening
by: Bhatia, Samarth, et al.
Published: (2024)

Representation learning in multiplex graphs: Where and how to fuse information?
by: Bielak, Piotr, et al.
Published: (2024)

Normalized mutual information is a biased measure for classification and community detection
by: Jerdee, Maximilian, et al.
Published: (2023)

Leveraging graph neural networks and mobility data for COVID-19 forecasting
by: Duarte, Fernando H. O., et al.
Published: (2025)

Improving the interpretability of GNN predictions through conformal-based graph sparsification
by: Sanchez-Martin, Pablo, et al.
Published: (2024)

Community detection in multiplex networks based on orthogonal nonnegative matrix tri-factorization
by: Ortiz-Bouza, Meiby, et al.
Published: (2022)

A graph neural network based on feature network for identifying influential nodes
by: Hu, Yanmei, et al.
Published: (2025)

Temporal social network modeling of mobile connectivity data with graph neural networks
by: Jaskari, Joel, et al.
Published: (2025)

GraphFM: A generalist graph transformer that learns transferable representations across diverse domains
by: Lachi, Divyansha, et al.
Published: (2024)

A family of graph GOSPA metrics for graphs with different sizes
by: Gu, Jinhao, et al.
Published: (2025)

Scalable inference of spatial regions and temporal signatures from time series
by: Weng, Jiayu, et al.
Published: (2026)

Robustness of graph embedding methods for community detection
by: Wei, Zhi-Feng, et al.
Published: (2024)

Graph Generation with $K^2$-trees
by: Jang, Yunhui, et al.
Published: (2023)

With a Little Help From My Friends: Collective Manipulation in Risk-Controlling Recommender Systems
by: De Toni, Giovanni, et al.
Published: (2026)

Using representation balancing to learn conditional-average dose responses from clustered data
by: Bockel-Rickermann, Christopher, et al.
Published: (2023)

An embedding-based distance for temporal graphs
by: Dall'Amico, Lorenzo, et al.
Published: (2024)

NetDiff: Deep Graph Denoising Diffusion for Ad Hoc Network Topology Generation
by: Marcoccia, Félix, et al.
Published: (2024)