:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Liu, Ziming, Liu, Longjian, Heidel, Robert E., Zhao, Xiaopeng
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2405.17502
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Nutritional influences on Alzheimer’s disease: Insights from transformer models and explainable AI
by: Ziming Liu, et al.
Published: (2024)

Explainable AI for Fair Sepsis Mortality Predictive Model
by: Chang, Chia-Hsuan, et al.
Published: (2024)

Do Two AI Scientists Agree?
by: Fu, Xinghong, et al.
Published: (2025)

Are Your Reasoning Models Reasoning or Guessing? A Mechanistic Analysis of Hierarchical Reasoning Models
by: Ren, Zirui, et al.
Published: (2026)

HyperSMOTE: A Hypergraph-based Oversampling Approach for Imbalanced Node Classifications
by: Zhao, Ziming, et al.
Published: (2024)

Explainability of Complex AI Models with Correlation Impact Ratio
by: Sengupta, Poushali, et al.
Published: (2026)

Using a Convolutional Neural Network and Explainable AI to Diagnose Dementia Based on MRI Scans
by: Morris, Tyler, et al.
Published: (2024)

Exploring the Plausibility of Hate and Counter Speech Detectors with Explainable AI
by: Böck, Adrian Jaques, et al.
Published: (2024)

Universal One-third Time Scaling in Learning Peaked Distributions
by: Liu, Yizhou, et al.
Published: (2026)

Iterative Refinement Neural Operators are Learned Fixed-Point Solvers: A Principled Approach to Spectral Bias Mitigation
by: Liu, Xiaotian, et al.
Published: (2026)

Stabilising Explainability Fragility in Cybersecurity AI: The Impact and Mitigation of Multicollinearity in Public Benchmark Datasets
by: Vourganas, Ioannis J., et al.
Published: (2026)

Superposition Yields Robust Neural Scaling
by: Liu, Yizhou, et al.
Published: (2025)

Explainable AI needs formalization
by: Haufe, Stefan, et al.
Published: (2024)

Exploring Machine Learning, Deep Learning, and Explainable AI Methods for Seasonal Precipitation Prediction in South America
by: Domingos, Matheus Corrêa, et al.
Published: (2025)

Explainable AI for Correct Root Cause Analysis of Product Quality in Injection Moulding
by: Muaz, Muhammad, et al.
Published: (2025)

Thermodynamic-Inspired Explainable GeoAI: Uncovering Regime-Dependent Mechanisms in Heterogeneous Spatial Systems
by: Lim, Sooyoung, et al.
Published: (2026)

An Explainable AI Framework for Dynamic Resource Management in Vehicular Network Slicing
by: Sun, Haochen, et al.
Published: (2025)

AI-Driven Predictive Analytics Approach for Early Prognosis of Chronic Kidney Disease Using Ensemble Learning and Explainable AI
by: Jawad, K M Tawsik, et al.
Published: (2024)

Explainable AI for Predicting and Understanding Mathematics Achievement: A Cross-National Analysis of PISA 2018
by: Liu, Liu, et al.
Published: (2025)

Enhancing SHAP Explainability for Diagnostic and Prognostic ML Models in Alzheimer Disease
by: Guillén, Pablo, et al.
Published: (2026)

Verifying Machine Unlearning with Explainable AI
by: Vidal, Àlex Pujol, et al.
Published: (2024)

Rethinking Explainability in the Era of Multimodal AI
by: Agarwal, Chirag
Published: (2025)

Explainable AI For Early Detection Of Sepsis
by: Thakur, Atharva, et al.
Published: (2025)

Explainable AI for Comparative Analysis of Intrusion Detection Models
by: Corea, Pap M., et al.
Published: (2024)

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs
by: Hsieh, Weiche, et al.
Published: (2024)

A Neural Scaling Law from Lottery Ticket Ensembling
by: Liu, Ziming, et al.
Published: (2023)

Towards Adversarially Robust Deep Metric Learning
by: Ke, Xiaopeng
Published: (2025)

Human-Computer Interaction and Human-AI Collaboration in Advanced Air Mobility: A Comprehensive Review
by: Sagirli, Fatma Yamac, et al.
Published: (2024)

Inverse Depth Scaling From Most Layers Being Similar
by: Liu, Yizhou, et al.
Published: (2026)

Analyzing the Impact of Adversarial Examples on Explainable Machine Learning
by: Devabhakthini, Prathyusha, et al.
Published: (2023)

Deep Learning Approaches with Explainable AI for Differentiating Alzheimer Disease and Mild Cognitive Impairment
by: Mostafa, Fahad, et al.
Published: (2025)

BERT-Based Approach for Automating Course Articulation Matrix Construction with Explainable AI
by: Shiferaw, Natenaile Asmamaw, et al.
Published: (2024)

Hierarchical Reference Sets for Robust Unsupervised Detection of Scattered and Clustered Outliers
by: Zhang, Yiqun, et al.
Published: (2026)

SE(3)-bi-equivariant Transformers for Point Cloud Assembly
by: Wang, Ziming, et al.
Published: (2024)

Exploring Feature Importance and Explainability Towards Enhanced ML-Based DoS Detection in AI Systems
by: Yakubu, Paul Badu, et al.
Published: (2024)

R-GenIMA: Integrating Neuroimaging and Genetics with Interpretable Multimodal AI for Alzheimer's Disease Progression
by: Zhao, Kun, et al.
Published: (2025)

Guided Game Level Repair via Explainable AI
by: Bazzaz, Mahsa, et al.
Published: (2024)

Neuro-Symbolic AI: Explainability, Challenges, and Future Trends
by: Zhang, Xin, et al.
Published: (2024)

Root Causing Prediction Anomalies Using Explainable AI
by: Vishnampet, Ramanathan, et al.
Published: (2024)

ExECG: An Explainable AI Framework for ECG models
by: Jang, Jong-Hwan, et al.
Published: (2026)