Cover Image

Interpretable Perturbation Modeling Through Biomedical Knowledge Graphs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Passigan, Pascal, Zhu, Kevin, Ning, Angelina
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Role of Graph Topology in the Performance of Biomedical Knowledge Graph Completion Models
by: Cattaneo, Alberto, et al.
Published: (2024)

CMKL: Modality-Aware Continual Learning for Evolving Biomedical Knowledge Graphs
by: Radwan, Yousef A., et al.
Published: (2026)

Learning to Denoise Biomedical Knowledge Graph for Robust Molecular Interaction Prediction
by: Ma, Tengfei, et al.
Published: (2023)

PrimeKG-CL: A Continual Graph Learning Benchmark on Evolving Biomedical Knowledge Graphs
by: Radwan, Yousef A., et al.
Published: (2026)

Injecting Structured Biomedical Knowledge into Language Models: Continual Pretraining vs. GraphRAG
by: Klila, Jaafer, et al.
Published: (2026)

Aligning LLMs with Biomedical Knowledge using Balanced Fine-Tuning
by: Tang, Zhenchao, et al.
Published: (2025)

Interpretable Question Answering with Knowledge Graphs
by: Aneja, Kartikeya, et al.
Published: (2025)

DeepEvidence: Empowering Biomedical Discovery with Deep Knowledge Graph Research
by: Wang, Zifeng, et al.
Published: (2025)

Online Detection of Anomalies in Temporal Knowledge Graphs with Interpretability
by: Zhang, Jiasheng, et al.
Published: (2024)

On the Relationship Between Interpretability and Explainability in Machine Learning
by: Leblanc, Benjamin, et al.
Published: (2023)

Unlocking Biomedical Insights: Hierarchical Attention Networks for High-Dimensional Data Interpretation
by: Nair, Rekha R, et al.
Published: (2025)

Medical Interpretability and Knowledge Maps of Large Language Models
by: Marinescu, Razvan, et al.
Published: (2025)

HeCiX: Integrating Knowledge Graphs and Large Language Models for Biomedical Research
by: Kulkarni, Prerana Sanjay, et al.
Published: (2024)

Reduction of Supervision for Biomedical Knowledge Discovery
by: Theodoropoulos, Christos, et al.
Published: (2025)

Croppable Knowledge Graph Embedding
by: Zhu, Yushan, et al.
Published: (2024)

Sparse Training of Discrete Diffusion Models for Graph Generation
by: Qin, Yiming, et al.
Published: (2023)

Unifying Adversarial Perturbation for Graph Neural Networks
by: Yang, Jinluan, et al.
Published: (2025)

Generating Multiple-Choice Knowledge Questions with Interpretable Difficulty Estimation using Knowledge Graphs and Large Language Models
by: Şakiroğlu, Mehmet Can, et al.
Published: (2026)

A Hierarchical Language Model For Interpretable Graph Reasoning
by: Khurana, Sambhav, et al.
Published: (2024)

Enhancing the Resilience of Graph Neural Networks to Topological Perturbations in Sparse Graphs
by: He, Shuqi, et al.
Published: (2024)

Temporal Inductive Path Neural Network for Temporal Knowledge Graph Reasoning
by: Dong, Hao, et al.
Published: (2023)

Graph Similarity Computation via Interpretable Neural Node Alignment
by: Wang, Jingjing, et al.
Published: (2024)

Graph-Based Adversarial Domain Generalization with Anatomical Correlation Knowledge for Cross-User Human Activity Recognition
by: Ye, Xiaozhou, et al.
Published: (2025)

Arbitrary Time Information Modeling via Polynomial Approximation for Temporal Knowledge Graph Embedding
by: Fang, Zhiyu, et al.
Published: (2024)

Geometric Structural Knowledge Graph Foundation Model
by: Xin, Ling, et al.
Published: (2025)

How Expressive are Knowledge Graph Foundation Models?
by: Huang, Xingyue, et al.
Published: (2025)

PerturbDiff: Functional Diffusion for Single-Cell Perturbation Modeling
by: Yuan, Xinyu, et al.
Published: (2026)

Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphs
by: Wang, Kai, et al.
Published: (2024)

RulE: Knowledge Graph Reasoning with Rule Embedding
by: Tang, Xiaojuan, et al.
Published: (2022)

SpherE: Expressive and Interpretable Knowledge Graph Embedding for Set Retrieval
by: Li, Zihao, et al.
Published: (2024)

The Unseen Threat: Residual Knowledge in Machine Unlearning under Perturbed Samples
by: Hsu, Hsiang, et al.
Published: (2026)

Global Concept Explanations for Graphs by Contrastive Learning
by: Teufel, Jonas, et al.
Published: (2024)

On the Wasserstein Gradient Flow Interpretation of Drifting Models
by: Gretton, Arthur, et al.
Published: (2026)

DrKGC: Dynamic Subgraph Retrieval-Augmented LLMs for Knowledge Graph Completion across General and Biomedical Domains
by: Xiao, Yongkang, et al.
Published: (2025)

A Survey of Few-Shot Learning for Biomedical Time Series
by: Li, Chenqi, et al.
Published: (2024)

Faithful Interpretation for Graph Neural Networks
by: Hu, Lijie, et al.
Published: (2024)

Meta-Models: An Architecture for Decoding LLM Behaviors Through Interpreted Embeddings and Natural Language
by: Costarelli, Anthony, et al.
Published: (2024)

Modeling Relational Patterns for Logical Query Answering over Knowledge Graphs
by: He, Yunjie, et al.
Published: (2023)

Federated Knowledge Graph Unlearning via Diffusion Model
by: Liu, Bingchen, et al.
Published: (2024)

Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning
by: Deuschel, Jannik, et al.
Published: (2023)