Saved in:
| Main Authors: | Pérez-Herrero, Adrián, Félix, Paulo, Presedo, Jesús, Ek, Carl Henrik |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.06919 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Comparative Evaluation of Explainable Machine Learning Versus Linear Regression for Predicting County-Level Lung Cancer Mortality Rate in the United States
by: Hashtarkhani, Soheil, et al.
Published: (2025)
by: Hashtarkhani, Soheil, et al.
Published: (2025)
NFCL: Simply interpretable neural networks for a short-term multivariate forecasting
by: Jo, Wonkeun, et al.
Published: (2024)
by: Jo, Wonkeun, et al.
Published: (2024)
Unsupervised Graph Deep Learning Reveals Emergent Flood Risk Profile of Urban Areas
by: Yin, Kai, et al.
Published: (2023)
by: Yin, Kai, et al.
Published: (2023)
Cryptogenic stroke and migraine: using probabilistic independence and machine learning to uncover latent sources of disease from the electronic health record
by: Betts, Joshua W., et al.
Published: (2025)
by: Betts, Joshua W., et al.
Published: (2025)
L-GTA: Latent Generative Modeling for Time Series Augmentation
by: Roque, Luis, et al.
Published: (2025)
by: Roque, Luis, et al.
Published: (2025)
A New Similarity Function for Spectral Clustering with Application to Plant Phenotypic Data
by: Ahuja, Kapil, et al.
Published: (2023)
by: Ahuja, Kapil, et al.
Published: (2023)
Cherry-Picking in Time Series Forecasting: How to Select Datasets to Make Your Model Shine
by: Roque, Luis, et al.
Published: (2024)
by: Roque, Luis, et al.
Published: (2024)
Feature graphs for interpretable unsupervised tree ensembles: centrality, interaction, and application in disease subtyping
by: Sirocchi, Christel, et al.
Published: (2024)
by: Sirocchi, Christel, et al.
Published: (2024)
Interactive Diabetes Risk Prediction Using Explainable Machine Learning: A Dash-Based Approach with SHAP, LIME, and Comorbidity Insights
by: Allani, Udaya
Published: (2025)
by: Allani, Udaya
Published: (2025)
Analyzing Geospatial and Socioeconomic Disparities in Breast Cancer Screening Among Populations in the United States: Machine Learning Approach
by: Hashtarkhani, Soheil, et al.
Published: (2025)
by: Hashtarkhani, Soheil, et al.
Published: (2025)
Decomposing Physician Disagreement in HealthBench
by: Borgohain, Satya, et al.
Published: (2026)
by: Borgohain, Satya, et al.
Published: (2026)
ASD-Bench: A Four-Axis Comprehensive Benchmark of AI Models for Autism Spectrum Disorder
by: Singh, Shubhankit, et al.
Published: (2026)
by: Singh, Shubhankit, et al.
Published: (2026)
Can Causal Discovery Algorithms Help in Generating Legal Arguments?
by: Wasmatkar, Soham, et al.
Published: (2026)
by: Wasmatkar, Soham, et al.
Published: (2026)
Macro-Level Correlational Analysis of Mental Disorders: Economy, Education, Society, and Technology Development
by: Tao, Yingzhi, et al.
Published: (2025)
by: Tao, Yingzhi, et al.
Published: (2025)
Entropy Causal Graphs for Multivariate Time Series Anomaly Detection
by: Febrinanto, Falih Gozi, et al.
Published: (2023)
by: Febrinanto, Falih Gozi, et al.
Published: (2023)
GCAD: Anomaly Detection in Multivariate Time Series from the Perspective of Granger Causality
by: Liu, Zehao, et al.
Published: (2025)
by: Liu, Zehao, et al.
Published: (2025)
Unsupervised Discovery of Clinical Disease Signatures Using Probabilistic Independence
by: Lasko, Thomas A., et al.
Published: (2024)
by: Lasko, Thomas A., et al.
Published: (2024)
Inter-Series Transformer: Attending to Products in Time Series Forecasting
by: Cristian, Rares, et al.
Published: (2024)
by: Cristian, Rares, et al.
Published: (2024)
A Self-explainable Model of Long Time Series by Extracting Informative Structured Causal Patterns
by: Wang, Ziqian, et al.
Published: (2025)
by: Wang, Ziqian, et al.
Published: (2025)
Assessing Electricity Demand Forecasting with Exogenous Data in Time Series Foundation Models
by: Cheong, Wei Soon, et al.
Published: (2026)
by: Cheong, Wei Soon, et al.
Published: (2026)
SCAFDS: Edge-Feature Graph Attention for Interbank Fraud Detection with Attribution-Grounded SAR Generation
by: Uddin, Mohammad Nasir
Published: (2026)
by: Uddin, Mohammad Nasir
Published: (2026)
Atlas-based Manifold Representations for Interpretable Riemannian Machine Learning
by: Robinett, Ryan A., et al.
Published: (2025)
by: Robinett, Ryan A., et al.
Published: (2025)
AMAD: AutoMasked Attention for Unsupervised Multivariate Time Series Anomaly Detection
by: Huang, Tiange, et al.
Published: (2025)
by: Huang, Tiange, et al.
Published: (2025)
SIBILA: A novel interpretable ensemble of general-purpose machine learning models applied to medical contexts
by: Banegas-Luna, Antonio Jesús, et al.
Published: (2022)
by: Banegas-Luna, Antonio Jesús, et al.
Published: (2022)
Uncovering Population PK Covariates from VAE-Generated Latent Spaces
by: Perazzolo, Diego, et al.
Published: (2025)
by: Perazzolo, Diego, et al.
Published: (2025)
Deep Policy Iteration with Integer Programming for Inventory Management
by: Harsha, Pavithra, et al.
Published: (2021)
by: Harsha, Pavithra, et al.
Published: (2021)
IFRA: a machine learning-based Instrumented Fall Risk Assessment Scale derived from Instrumented Timed Up and Go test in stroke patients
by: Macciò, Simone, et al.
Published: (2025)
by: Macciò, Simone, et al.
Published: (2025)
A Standardized Benchmark for Multilabel Antimicrobial Peptide Classification
by: Ojeda, Sebastian, et al.
Published: (2025)
by: Ojeda, Sebastian, et al.
Published: (2025)
Why Aggregate Accuracy is Inadequate for Evaluating Fairness in Law Enforcement Facial Recognition Systems
by: Alsayed, Khalid Adnan
Published: (2026)
by: Alsayed, Khalid Adnan
Published: (2026)
DecompKAN: Decomposed Patch-KAN for Long-Term Time Series Forecasting
by: Mysore, Naveen
Published: (2026)
by: Mysore, Naveen
Published: (2026)
Static Seeding and Clustering of LSTM Embeddings to Learn from Loosely Time-Decoupled Events
by: Manasseh, Christian, et al.
Published: (2022)
by: Manasseh, Christian, et al.
Published: (2022)
Automating the Deep Space Network Data Systems; A Case Study in Adaptive Anomaly Detection through Agentic AI
by: Chou, Evan J., et al.
Published: (2025)
by: Chou, Evan J., et al.
Published: (2025)
STLLM-DF: A Spatial-Temporal Large Language Model with Diffusion for Enhanced Multi-Mode Traffic System Forecasting
by: Shao, Zhiqi, et al.
Published: (2024)
by: Shao, Zhiqi, et al.
Published: (2024)
Model Fusion via Retrofitting
by: Luenam, Phoomraphee, et al.
Published: (2025)
by: Luenam, Phoomraphee, et al.
Published: (2025)
Improving Omics-Based Classification: The Role of Feature Selection and Synthetic Data Generation
by: Perazzolo, Diego, et al.
Published: (2025)
by: Perazzolo, Diego, et al.
Published: (2025)
Diffusion-Based Scenario Tree Generation for Multivariate Time Series Prediction and Multistage Stochastic Optimization
by: Zarifis, Stelios, et al.
Published: (2025)
by: Zarifis, Stelios, et al.
Published: (2025)
Smart and Efficient IoT-Based Irrigation System Design: Utilizing a Hybrid Agent-Based and System Dynamics Approach
by: Pargo, Taha Ahmadi, et al.
Published: (2025)
by: Pargo, Taha Ahmadi, et al.
Published: (2025)
FORCE: Feature-Oriented Representation with Clustering and Explanation
by: Mukherjee, Rishav, et al.
Published: (2025)
by: Mukherjee, Rishav, et al.
Published: (2025)
A Hybrid Model for Stock Market Forecasting: Integrating News Sentiment and Time Series Data with Graph Neural Networks
by: Sadek, Nader, et al.
Published: (2025)
by: Sadek, Nader, et al.
Published: (2025)
Precision at Scale: Domain-Specific Datasets On-Demand
by: Rodríguez-de-Vera, Jesús M, et al.
Published: (2024)
by: Rodríguez-de-Vera, Jesús M, et al.
Published: (2024)
Similar Items
-
Comparative Evaluation of Explainable Machine Learning Versus Linear Regression for Predicting County-Level Lung Cancer Mortality Rate in the United States
by: Hashtarkhani, Soheil, et al.
Published: (2025) -
NFCL: Simply interpretable neural networks for a short-term multivariate forecasting
by: Jo, Wonkeun, et al.
Published: (2024) -
Unsupervised Graph Deep Learning Reveals Emergent Flood Risk Profile of Urban Areas
by: Yin, Kai, et al.
Published: (2023) -
Cryptogenic stroke and migraine: using probabilistic independence and machine learning to uncover latent sources of disease from the electronic health record
by: Betts, Joshua W., et al.
Published: (2025) -
L-GTA: Latent Generative Modeling for Time Series Augmentation
by: Roque, Luis, et al.
Published: (2025)